Effect of Nitrogen Fertigation by Sprinkler Irrigation on Sugar Beet Crop Performance

It is crucial to make field management strategy by understanding of spatial and temporal variability of effective elements such as soil, water and plant properties. The impact of nitrogen fertigation by sprinkler irrigation would be a valuable step in support of environmental preservation and natural resources conservation. This research has focused on the spatial and temporal distribution of N fertigation by sprinkler irrigation and its effect on soil and plant properties to determine the relationship among fertigation distribution pattern and crop performance. The field variability study was carried out in the Fesaran village in east part of Esfahan city in Esfahan Province, Iran. Geostatistical sampling method was selected for an accurate interpolation by kriging to produce spatial and temporal variability maps. A total of 162 soil samples and 81 plant samples were collected and locations recorded using Differential Global Positioning System (DGPS). To describe the variability of soil and plant status, soil and plant nutrient response to the nitrogen fertilizer application by sprinklers was studied by analyzing 7 soil elements including N, P, K, CEC, OM, EC, and PH under two conditions, pre-treatment (before fertigation) and posttreatment (after fertigation). The sugar beet crop performance was based on 6 crop properties that include leaf N content, tuber moisture content, tuber sugar content, tuber weight, number of tubers in each square meter and yield. Variability maps were obtained using Geographical Information System (GIS) and Geostatistical statistics (GS+) software. Statistical analysis, geostatistical analysis and spatial analysis were employed to analyze the data. Data statistical analysis consist of descriptive analysis, T-Test (Pairwise two-tail), correlation (Pearson two-tail) and ANOVA (Duncan and SNK) and regression were derived from Statistical Package for the Social Sciences (SPSS) and Statistical Analysis System (SAS) software. The impact of N fertigation through sprinkler irrigation on spatial and temporal pattern of soil properties and spatial variability of sugar beet crop performance was studied through statistical analysis and visualization of spatial variability maps. The results show that the highest variability in available P (CV =89.7 %) and K (CV =53.26 %) between selected soil properties. It could be related to non-uniform fertilization of potash and phosphate pre-plant that were applied manually. The least variability was seen in soil pH (CV =0.97 %) and soil OM (CV =3.04 %).That is an evidence of very low variability of soil pH and OM through and across the study area. Low variability of soil N (CV =12.44 %, CV =14.7 %) would be a key point to encourage farmers to replace fertigation by sprinkler irrigation instead of current methods.The highest variability of crop properties belonged to tuber weight (CV=44.8 %) while the least variability was in tuber moisture content (CV=6.04 %) and tuber sugar content (CV=6.38 %) which points out the low variability of sugar and moisture content of tubers. Crop properties such as yield, tuber sugar content, tuber numbers, tuber moisture content and N leaf content have low variability (CV ≤ 25 %), except tuber weight with moderate variability. Spatial variability map displays concentration of the higher yield was seen in central area compared to least yield in the north west of the study area. Fewer tubers in the north and east of the study area compared to more tubers in the south and west. Interestingly, for those areas which have heavier tubers, the map shows fewer numbers of tubers. Plant performance analysis shows a negative significant correlation of leaf N content with sugar content of tuber at 95 % confidence. Tuber weight has a negative correlation to the number of tubers but positive correlation to the tuber moisture content. It indicates the higher moisture content causes heavier tuber but the grid which has more number of tubers has the lighter tubers. There is a negative correlation of tuber weight and number of tubers but positive significant correlation of number of tubers and sugar content. It indicates that more tubers with lighter weight have higher sugar content. Surprising result shows the negative correlation of leaf N content and sugar content

Assessing the utility of geospatial technologies to investigate environmental change within lake systems

Over 50% of the world's population live within 3. km of rivers and lakes highlighting the on-going importance of freshwater resources to human health and societal well-being. Whilst covering c. 3.5% of the Earth's non-glaciated land mass, trends in the environmental quality of the world's standing waters (natural lakes and reservoirs) are poorly understood, at least in comparison with rivers, and so evaluation of their current condition and sensitivity to change are global priorities. Here it is argued that a geospatial approach harnessing existing global datasets, along with new generation remote sensing products, offers the basis to characterise trajectories of change in lake properties e.g., water quality, physical structure, hydrological regime and ecological behaviour. This approach furthermore provides the evidence base to understand the relative importance of climatic forcing and/or changing catchment processes, e.g. land cover and soil moisture data, which coupled with climate data provide the basis to model regional water balance and runoff estimates over time. Using examples derived primarily from the Danube Basin but also other parts of the World, we demonstrate the power of the approach and its utility to assess the sensitivity of lake systems to environmental change, and hence better manage these key resources in the future

Evaporite karst geohazards in the Delaware Basin, Texas: review of traditional karst studies coupled with geophysical and remote sensing characterization

Evaporite karst throughout the Gypsum Plain of west Texas is complex and extensive, including manifestations ranging from intrastratal brecciation and hypogene caves to epigene features and suffosion caves. Recent advances in hydrocarbon exploration and extraction has resulted in increased infrastructure development and utilization in the area; as a result, delineation and characterization of potential karst geohazards throughout the region have become a greater concern. While traditional karst surveys are essential for delineating the subsurface extent and morphology of individual caves for speleogenetic interpretation, these methods tend to underestimate the total extent of karst development and require surficial manifestation of karst phenomena. Therefore, this study utilizes a composite suite of remote sensing and traditional field studies for improved karst delineation and detection of potential karst geohazards within gypsum karst. Color InfraRed (CIR) imagery were utilized for delineation of lineaments associated with fractures, while Normalized Density Vegetation Index (NDVI) analyses were used to delineate regions of increased moisture flux and probable zones of shallow karst development. Digital Elevation Models (DEM) constructed from high-resolution LiDAR (Light Detection and Ranging) data were used to spatially interpret sinkholes, while analyses of LiDAR intensity data were used in a novel way to categorize local variations in surface geology. Resistivity data, including both direct current (DC) and capacitively coupled (CC) resistivity analyses, were acquired and interpreted throughout the study area to delineate potential shallow karst geohazards specifically associated with roadways of geohazard concern; however, detailed knowledge of the surrounding geology and local karst development proved essential for proper interpretation of resistivity inversions. The composite suite of traditional field investigations and remotely sensed karst delineations used in this study illustrate how complex gypsum karst terrains can be characterized with greater detail through the utilization of rapidly advancing technologies, especially in arid environments with low vegetation densities

Identification of Optimal Locations for Sampling Ground Water for Pesticides in the Mississippi Delta Region of Eastern Arkansas

Concerns about the presence of pesticides in the Mississippi River Valley alluvial aquifer in the Arkansas Delta have generated the need to develop a map of ground water vulnerability for this region comprised of approximately 10 million acres. Based on the availability of digital data and the scale of this study. we used a modified Pesticide DRASTIC model in a GRASS GIS environment to identify areas that were physically more sensitive to pesticide contamination than other areas within the Delta. Spatial distribution of pesticide loading was estimated from pesticide application rates in different crops and crop distribution map interpreted from satellite imagery. Relative ground water vulnerability index was expressed as a product of aquifer sensitivity index and pesticide loading index. The resulting map showing the spatial distribution of relative ground water vulnerability index values was intended for use in selecting optimal locations for sampling ground water for pesticides in the Arkansas Delta and for aid in implementing the Arkansas Agricultural Chemical Ground-Water Management Plan. The most sensitive areas in the Delta are distributed mostly along major streams where a combination of shallow depth to ground water, thin confining unit, permeable soils, and high recharge rate usually prevails. It is also in many of these areas where large acres of crops are grown, and pesticides are used. Consequently, many areas along major streams are also most vulnerable. These vulnerable areas may be targeted by planners and governmental agencies for further detailed evaluation. Uncertainties in the methodology and mapped input data, plus the dynamic nature of model factors, require continued and improved efforts in ground water vulnerability assessment for the Arkansas Delta

Identifying Advantages and Disadvantages of Variable Rate Irrigation – An Updated Review

Variable rate irrigation (VRI) sprinklers on mechanical move irrigation systems (center pivot or lateral move) have been commercially available since 2004. Although the number of VRI, zone or individual sprinkler, systems adopted to date is lower than expected there is a continued interest to harness this technology, especially when climate variability, regulatory nutrient management, water conservation policies, and declining water for agriculture compound the challenges involved for irrigated crop production. This article reviews the potential advantages and potential disadvantages of VRI technology for moving sprinklers, provides updated examples on such aspects, suggests a protocol for designing and implementing VRI technology and reports on the recent advancements. The advantages of VRI technology are demonstrated in the areas of agronomic improvement, greater economic returns, environmental protection and risk management, while the main drawbacks to VRI technology include the complexity to successfully implement the technology and the lack of evidence that it assures better performance in net profit or water savings. Although advances have been made in VRI technologies, its penetration into the market will continue to depend on tangible and perceived benefits by producers

Soil erosion in the Alps : causes and risk assessment

The issue of soil erosion in the Alps has long been neglected due to the low economic value of the agricultural land. However, soil stability is a key parameter which affects ecosystem services like slope stability, water budgets (drinking water reservoirs as well as flood prevention), vegetation productivity, ecosystem biodiversity and nutrient production. In alpine regions, spatial estimates on soil erosion are difficult to derive because the highly heterogeneous biogeophysical structure impedes measurement of soil erosion and the applicability of soil erosion models. However, remote sensing and geographic information system (GIS) methods allow for spatial estimation of soil erosion by direct detection of erosion features and supply of input data for soil erosion models. Thus, the main objective of this work is to address the problem of soil erosion risk assessment in the Alps on catchment scale with remote sensing and GIS tools. Regarding soil erosion processes the focus is on soil erosion by water (here sheet erosion) and gravity (here landslides). For these two processes we address i) the monitoring and mapping of the erosion features and related causal factors ii) soil erosion risk assessment with special emphasis on iii) the validation of existing models for alpine areas. All investigations were accomplished in the Urseren Valley (Central Swiss Alps) where the valley slopes are dramatically affected by sheet erosion and landslides. For landslides, a natural susceptibility of the catchment has been indicated by bivariate and multivariate statistical analysis. Geology, slope and stream density are the most significant static landslide causal factors. Static factors are here defined as factors that do not change their attributes during the considered time span of the study (45 years), e.g. geology, stream network. The occurrence of landslides might be significantly increased by the combined effects of global climate and land use change. Thus, our hypothesis is that more recent changes in land use and climate affected the spatial and temporal occurrence of landslides. The increase of the landslide area of 92% within 45 years in the study site confirmed our hypothesis. In order to identify the cause for the trend in landslide occurrence time-series of landslide causal factors were analysed. The analysis revealed increasing trends in the frequency and intensity of extreme rainfall events and stocking of pasture animals. These developments presumably enhanced landslide hazard. Moreover, changes in land-cover and land use were shown to have affected landslide occurrence. For instance, abandoned areas and areas with recently emerging shrub vegetation show very low landslide densities. Detailed spatial analysis of the land use with GIS and interviews with farmers confirmed the strong influence of the land use management practises on slope stability. The definite identification and quantification of the impact of these non-stationary landslide causal factors (dynamic factors) on the landslide trend was not possible due to the simultaneous change of several factors. The consideration of dynamic factors in statistical landslide susceptibility assessments is still unsolved. The latter may lead to erroneous model predictions, especially in times of dramatic environmental change. Thus, we evaluated the effect of dynamic landslide causal factors on the validity of landslide susceptibility maps for spatial and temporal predictions. For this purpose, a logistic regression model based on data of the year 2000 was set up. The resulting landslide susceptibility map was valid for spatial predictions. However, the model failed to predict the landslides that occurred in a subsequent event. In order to handle this weakness of statistic landslide modelling a multitemporal approach was developed. It is based on establishing logistic regression models for two points in time (here 1959 and 2000). Both models could correctly classify >70% of the independent spatial validation dataset. By subtracting the 1959 susceptibility map from the 2000 susceptibility map a deviation susceptibility map was obtained. Our interpretation was that these susceptibility deviations indicate the effect of dynamic causal factors on the landslide probability. The deviation map explained 85% of new independent landslides occurring after 2000. Thus, we believe it to be a suitable tool to add a time element to a susceptibility map pointing to areas with changing susceptibility due to recently changing environmental conditions or human interactions. In contrast to landslides that are a direct threat to buildings and infrastructure, sheet erosion attracts less attention because it is often an unseen process. Nonetheless, sheet erosion may account for a major proportion of soil loss. Soil loss by sheet erosion is related to high spatial variability, however, in contrast to arable fields for alpine grasslands erosion damages are long lasting and visible over longer time periods. A crucial erosion triggering parameter that can be derived from satellite imagery is fractional vegetation cover (FVC). Measurements of the radiogenic isotope Cs-137, which is a common tracer for soil erosion, confirm the importance of FVC for soil erosion yield in alpine areas. Linear spectral unmixing (LSU), mixture tuned matched filtering (MTMF) and the spectral index NDVI are applied for estimating fractional abundance of vegetation and bare soil. To account for the small scale heterogeneity of the alpine landscape very high resolved multispectral QuickBird imagery is used. The performance of LSU and MTMF for estimating percent vegetation cover is good (r²=0.85, r²=0.71 respectively). A poorer performance is achieved for bare soil (r²=0.28, r²=0.39 respectively) because compared to vegetation, bare soil has a less characteristic spectral signature in the wavelength domain detected by the QuickBird sensor. Apart from monitoring erosion controlling factors, quantification of soil erosion by applying soil erosion risk models is done. The performance of the two established models Universal Soil Loss Equation (USLE) and Pan-European Soil Erosion Risk Assessment (PESERA) for their suitability to model erosion for mountain environments is tested. Cs-137 is used to verify the resulting erosion rates from USLE and PESERA. PESERA yields no correlation to measured Cs-137 long term erosion rates and shows lower sensitivity to FVC. Thus, USLE is used to model the entire study site. The LSU-derived FVC map is used to adapt the C factor of the USLE. Compared to the low erosion rates computed with the former available low resolution dataset (1:25000) the satellite supported USLE map shows “hotspots” of soil erosion of up to 16 t ha-1 a-1. In general, Cs-137 in combination with the USLE is a very suitable method to assess soil erosion for larger areas, as both give estimates on long-term soil erosion. Especially for inaccessible alpine areas, GIS and remote sensing proved to be powerful tools that can be used for repetitive measurements of erosion features and causal factors. In times of global change it is of crucial importance to account for temporal developments. However, the evaluation of the applied soil erosion risk models revealed that the implementation of temporal aspects, such as varying climate, land use and vegetation cover is still insufficient. Thus, the proposed validation strategies (spatial, temporal and via Cs-137) are essential. Further case studies in alpine regions are needed to test the methods elaborated for the Urseren Valley. However, the presented approaches are promising with respect to improve the monitoring and identification of soil erosion risk areas in alpine regions

Spatial aspects of the design and targeting of agricultural development strategies:

Two increasingly shared perspectives within the international development community are that (a) geography matters, and (b) many government interventions would be more successful if they were better targeted. This paper unites these two notions by exploring the opportunities for, and benefits of, bringing an explicitly spatial dimension to the tasks of formulating and evaluating agricultural development strategies. We first review the lingua franca of land fragility and find it lacking in its capacity to describe the dynamic interface between the biophysical and socioeconomic factors that help shape rural development options. Subsequently, we propose a two-phased approach. First, development strategy options are characterized to identify the desirable ranges of conditions that would most favor successful strategy implementation. Second, those conditions exhibiting important spatial dependency – such as agricultural potential, population density, and access to infrastructure and markets – are matched against a similarly characterized, spatially-referenced (GIS) database. This process generates both spatial (map) and tabular representations of strategy-specific development domains. An important benefit of a spatial (GIS) framework is that it provides a powerful means of organizing and integrating a very diverse range of disciplinary and data inputs. At a more conceptual level we propose that it is the characterization of location, not the narrowly-focused characterization of land, that is more properly the focus of attention from a development perspective. The paper includes appropriate examples of spatial analysis using data from East Africa and Burkina Faso, and concludes with an appendix describing and interpreting regional climate and soil data for Sub-Saharan Africa that was directly relevant to our original goal.Spatial analysis (Statistics), Agricultural development., Burkina Faso., Africa, Sub-Saharan.,