Combined use of remote sensing and GIS for degradation risk assessment in some soils of the Northern Nile Delta, Egypt

The present study aimed to assess the potential of Remote Sensing (RS) and Geographic Information System (GIS) to quantify soil degradation risk in some soils of the Northern Nile Delta. Physiographic units were mapped using Landsat ETM+ image (2003) and Digital Elevation Model (DEM). The obtained map showed that the study area comprised two distinct landscapes i.e. fluvial lacustrine and flood plains. The main landforms of the area under consideration are grouped as decantation basins, levees, recent river terraces, overflow basins, man-made terraces, fish ponds and turtle backs. A simple model was designed for assessing risk of land degradation depending on the equations of soil and climatic factors. The study demonstrated that about 48.09% of the study area has undergone very high risk of chemical degradation, whereas 51.91% of the area has undergone low risk of chemical degradation. About 20.12% of the total area was characterized by high risk of physical degradation. The results indicated that the salinity, alkalinity and water logging are the main common degradation hazards

An approach for precision farming under pivot irrigation system using remote sensing and GIS techniques

The current work is aimed to realizing land and water use efficiency and determining the profitability of precision farming economically and environmentally. The studied area is represented by an experimental pivot irrigation field cultivated with maize in Ismailia province, Egypt. Two field practices were carried out during the successive summer growing seasons (2008 and 2009) to study the response of maize plants single hybrid 10 (S.H.10) to traditional and precision farming practices. Traditional farming (TF) as handled by the farm workers were observed and noted carefully. On the other hand precision farming (PF) practices included field scouting, grid soil sampling, variable rate technology and its applications. After applying PF a dramatic change in management zones was noticed and three management zones (of total four) were merged to be more homogenous representing 84.3% of the pivot irrigation field. Under PF Remote Sensing and Geographic Information System techniques have played a vital role in the variable rate applications that were defined due to management zones requirements. Fertilizers were added in variable rates, so that rationalization of fertilizers saved 23.566 tonnes/experimental pivot area. Natural drainage system was improved by designing vertical holes to break down massive soil layers and to leach excessive salts. Crop water requirements were determined in variable rate according to the actual plant requirements using SEBAL model with the aid of FAO Cropwat model. Irrigation schedule of maize was adopted considering soil water retention, depletion, gross and net irrigation saving an amount of water equal to 93,718 m3 in the pivot irrigation field (153.79 acre). However costs of applying PF were much higher than TF, the economic profitability (returns-costs) achieved remarkable increase of 29.89% as a result of crop yield increment by 1000, 2100, 800 and 200 kg/acre in the management zones 1, 2, 3 and 4, respectively. Finally applying adequate amounts of fertilizers beside water control the environmental hazards was reduced to the acceptable limits.Precision farming SEBAL Cropwat Management zone Remote sensing and GIS

Vis‐nir spectroscopy and satellite landsat‐8 oli data to map soil nutrients in arid conditions: A case study of the northwest coast of egypt

The mapping of soil nutrients is a key issue for numerous applications and research fields ranging from global changes to environmental degradation, from sustainable soil management to the precision agriculture concept. The characterization, modeling and mapping of soil properties at diverse spatial and temporal scales are key factors required for different environments. This paper is focused on the use and comparison of soil chemical analyses, Visible near infrared and shortwave infrared VNIR‐SWIR spectroscopy, partial least‐squares regression (PLSR), Ordinary Kriging (OK), and Landsat‐8 operational land imager (OLI) images, to inexpensively analyze and predict the content of different soil nutrients (nitrogen (N), phosphorus (P), and potassium (K)), pH, and soil organic matter (SOM) in arid conditions. To achieve this aim, 100 surface samples of soil were gathered to a depth of 25 cm in the Wadi El‐Garawla area (the northwest coast of Egypt) using chemical analyses and reflectance spectroscopy in the wavelength range from 350 to 2500 nm. PLSR was used firstly to model the relationship between the averaged values from the ASD spectroradiometer and the available N, P, and K, pH and SOM contents in soils in order to map the predicted value using Ordinary Kriging (OK) and secondly to retrieve N, P, K, pH, and SOM values from OLI images. Thirty soil samples were selected to verify the validity of the results. The randomly selected samples included the spatial diversity and characteristics of the study area. The prediction of available of N, P, K pH and SOM in soils using VNIR‐SWIR spectroscopy showed high performance (where R2 was 0.89, 0.72, 0.91, 0.65, and 0.75, respectively) and quite satisfactory results from Landsat‐8 OLI images (correlation R2 values 0.71, 0.68, 0.55, 0.62 and 0.7, respectively). The results showed that about 84% of the soils of Wadi El‐Garawla are characterized by low‐to‐moderate fertility, while about 16% of the area is characterized by high soil fertility. © MDPI AG. All rights reserved

Impacts of rising temperature, carbon dioxide concentration and sea level on wheat production in North Nile delta

Climate change poses a serious threat to arid and low elevation coastal zones. Kafrelsheikh governorate, as a large agricultural and coastal region on the Egyptian North Nile Delta, is one of the most vulnerable areas to higher temperature and global sea level rise. Two DSSAT wheat models (CERES and N-Wheat) were calibrated using a local cultivar (Misr3) grown under irrigated conditions in Egypt. Experimental data of two successive growing seasons during 2014/2015 and 2015/2016 were used for calibration using different treatments of irrigation, planting dates and fertilization. Both models simulated the phenology and wheat yield well, with root mean square deviation of b10%, and d-index N 0.80. Climate change sensitivity analysis showed that rising temperature by 1 °C to 4 °C decreased wheat yield by 17.6%. However, elevated atmospheric CO2 concentrations increased yield and could overtake some of the negative temperature responses. Sea level rise by 2.0 m will reduce the extent of agricultural land on the North Nile Delta of Egypt by ~60% creating an additional challenge to wheat production in this region.Agricultural Research Center, Egyp

Modeling land suitability for rice crop using remote sensing and soil quality indicators: The case study of the nile delta

Today, the global food security is one of the most pressing issues for humanity, and, according to Food and Agriculture Organisation (FAO), the increasing demand for food is likely to grow by 70% until 2050. In this current condition and future scenario, the agricultural production is a critical factor for global food security and for facing the food security challenge, with specific reference to many African countries, where a large quantities of rice are imported from other continents. According to FAO, to face the Africa’s inability to reach self-sufficiency in rice, it is urgent “to redress to stem the trend of over-reliance on imports and to satisfy the increasing demand for rice in areas where the potential of local production resources is exploited at very low levels” The present study was undertaken to design a new method for land evaluation based on soil quality indicators and remote sensing data, to assess and map soil suitability for rice crop. Results from the investigations, performed in some areas in the northern part of the Nile Delta, were compared with the most common approaches, two parametric (the square root, Storie methods) and two qualitative (ALES and MicrioLEIS) methods. From the qualitative point of view, the results showed that: (i) all the models provided partly similar outputs related to the soil quality assessments, so that the distinction using the crop productivity played an important role, and (ii) outputs from the soil suitability models were consistent with both the satellite Sentinel-2 Normalize Difference Vegetation Indices (NDVI) during the crop growth and the yield production. From the quantitative point of view, the comparison of the results from the diverse approaches well fit each other, and the model, herein proposed, provided the highest performance. As a whole, a significant increasing in R2 values was provided by the model herein proposed, with R2 equal to 0.92, followed by MicroLES, Storie, ALES and Root as R2 with value equal to 0.87, 0.86, 0.84 and 0.84, respectively, with increasing percentage in R2 equal to 5%, 6% and 8%, respectively. Furthermore, the proposed model illustrated that around (i) 44.44% of the total soils of the study area are highly suitable, (ii) 44% are moderately suitable, and (iii) approximately 11.56% are unsuitable for rice due to their adverse physical and chemical soil properties. The approach herein presented can be promptly re-applied in arid region and the quantitative results obtained can be used by decision makers and regional governments. © 2020 by the authors. Licensee MDPI, Basel, Switzerland