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Review Article GIS-based land degradation risk assessment of governorate,

* M.I. El-Gammal a, R.R. Ali b, R.M. Abou Samra a,

a Environmental Science Department, Faculty of Science, Damietta University, Egypt b Soils and Water Use Department, National Research Centre, , Egypt

article info abstract

Article history: This study aims to assess the land degradation risk in the governorate by using Received 23 March 2014 Geographical Information System (GIS) technique. The preliminary landforms of the area Received in revised form were defined by using remote sensing data. The area includes flood plain, lacustrine plain 23 January 2015 and marine plain. A total of 18 soil profiles representing different mapping units were Accepted 25 January 2015 studied. Thirty six soil samples were collected for laboratory analysis. The soil properties of Available online 11 February 2015 bulk density and electrical conductivity (EC) were attached to the different landforms. The thematic layers of these properties were created in Arc-GIS 10.2 software using the spatial Keywords: analysis function and then these layers were matched together to assess the soil degra- Damietta governorate dation. The obtained results revealed that the high risk of physical (i.e. soil compaction) Land degradation risk and chemical vulnerability (i.e. salinization) covered an area of 86.02 km2 (12.83%) and Soil salinity 2.28 km2 (0.34%), respectively in the surface soil layers. The land degradation hazard in the Soil compaction surface layers due to soil compaction was moderate to very high, whereas the degree of Geographic information system salinization was low to high. Regarding to the subsurface soil layers, the high risk of physical degradation and chemical degradation covered an area of 127.8 km2 (19.06%) and 10.6 km2 (1.58%), respectively. The land degradation hazard due to soil compaction in the subsurface layers was moderate to high, whereas the degree of salinization was low to very high. Copyright 2015, Mansoura University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/ by-nc-nd/4.0/).

exposed to degradation processes [3]. Land degradation, 1. Introduction defined as a reduction in the biological productivity of land arising from climate change and human activities, is a serious Land is the most valuable natural resource for production of environmental problem [4]. The cultivated land represents food, fuel and many other essential goods that are required to about 40e50 % of the global [5], 20% of them are severely meet human and animal needs [1]. Soils are limited resource degraded [6,7]. In irrigated agriculture lands under the arid and could be considered nonrenewable [2]; it is continuously climate, water logging and salinization are the major land

* Corresponding author. Tel.: þ20 1229987476; fax: þ20 57 2403868. E-mail address: [email protected] (R.M. Abou Samra). Peer review under responsibility of Mansoura University. http://dx.doi.org/10.1016/j.ejbas.2015.01.001 2314-808X/Copyright 2015, Mansoura University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY- NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 184 egyptian journal of basic and applied sciences 2 (2015) 183e189

degradation processes [8]. Most of these processes are directly affected by human activities [9,10]. Land degradation leads to a gradual decrease in soil productivity [11], hindering sus- tainable development [12,13] and consequently food gap are expected [14]. The main types of land degradation identified in Egypt are salinity, sodicity, compaction and water logging [15]. The alarming losses in economic revenues and agro- ecosystem services have revealed an acute need for moni- toring of land degradation and analyses of its causes in order to advise decision makers on spatial targeting of land reha- bilitation measures [16]. This study aims to address the land degradation risk of Damietta governorate. Land surveying data, laboratory analyses, remote sensing and GIS were the main tools used to fulfill this objective.

Fig. 2 e Locations of soil profiles over the landforms of 2. Materials and methods Damietta governorate, modified after Ali and Shalaby [19].

2.1. The study area

1:25,000) the landform map of the area was produced by Ali Damietta governorate is located at the northeast of the 0 0 0 and Shalaby [19]. Following the methodology developed by Delta between longitudes 31 28 & 32 04 and latitude 31 10 & 0 Dobos et al. [20], the different landform units were checked 31 30 (Fig. 1). The governorate covers an area of 227575.32 and updated during the field work. acres, representing 0.1% of the Republic's area, and encom- passes 4 districts, 10 cities, 47 rural units and 85 villages. Ac- 2.3. Field work and laboratory analyses cording to the preliminary results of 2006 census, population is about 1.1 million people; 38.4% of them live in urban areas - A semi detailed survey was carried out throughout the and 61.6% in rural areas. The governorate cultivated area investigated area in order to gain an appreciation on soil covers 108.8 thousand acres and is famous for growing wheat, patterns. A total of 18 ground truth sites were studied in the maize, cotton, rice, potatoes, lemons, grapes, and tomatoes field, from which 18 soil profiles and 36 soil samples were [17]. collected to represent the different landform units (Fig. 2). - Soils samples were analyzed following the procedure 2.2. Digital image processing detailed by USDA [21] and Klute [22]. - The land surveying and laboratory analyses data were - In this study Landsat-8 image (path 176, row 038) acquired recorded in the attribute table of the landform map using during the year 2013 was used. Image was radiometrically Arc-GIS 10.2 software. and geometrically corrected to accurate the irregular sensor response over the image and to correct the geo- 2.4. Spatial distribution of soil properties metric distortion due to Earth's rotation [18]. - Using the satellite data and the digital elevation model Spatial interpolation is commonly used for producing (extracted from the available contour maps at scale continuous information when data are collected at distinct

Fig. 1 e Location of Damietta governorate on Egypt map (left), Landsat-8 Image of the governorate acquired in 2013 (right). egyptian journal of basic and applied sciences 2 (2015) 183e189 185

2.5. Soil degradation assessment Table 1 e Classes of soil degradation risk.

Hazard Indicator Unit Risk class Land degradation risk was assessed following the methodol- type Low Moderate High Very ogy developed by FAO [24] and UNEP [25]. Table 1 illustrates high the risk of land degradation which depends on the EC and bulk Salinization EC dS/m <44e88e16 >16 density values. Compaction Bulk g/cm3 <1.2 1.2e1.4 1.4e1.6 >1.6 density

3. Results and discussion locations (e.g. soil profiles). The inverse distance weighted (IDW) is an interpolation method, which weighs the sur- 3.1. Landforms rounding known values to derive estimations for an unmea- sured location. However, the weights are based not only on Three landscapes were recognizing in the study area i.e. flood the distance between the known points and the unmeasured plain, lacustrine plain and marine plain. The flood plain point but also on the overall geostatistical relationships dominates the southern parts including low elevated river among the known points [23]. Arc-GIS 10.2 software has terraces, high elevated river terraces, river levee, overflow been used to interpolate the soil properties i.e. electrical mantle, decantation basin and overflow basin. Marine plain conductivity (EC); soils pH; and bulk density using the IDW exhibit the northern parts, comprises the units of high method. elevated sand sheet, low elevated sand sheet, sandy beach,

Table 2 e Some physical and chemical characteristics of the studied soil profiles. Profile No. Landform Depth (cm) EC pH Texture class Bulk density g/cm3 (1:1) (1:2.5) dS m 1 1 Overflow basin 0e30 2.2 7.9 C 1.24 30e60 2.2 8.0 C 1.27 2 Overflow basin 0e30 1.9 8.2 C 1.26 30e60 2.1 8.2 C 1.31 3 Overflow basin 0e30 2.8 8.63 CL 1.33 30e60 3 8.7 CL 1.29 4 Overflow mantle 0e30 3.9 8.5 CL 1.29 30e60 3.3 8.0 CL 1.3 5 Overflow mantle 0e30 2.6 7.6 CL 1.28 30e60 2.4 7.8 CL 1.32 6 Overflow mantle 0e30 2.3 7.9 CL 1.40 30e60 2.4 7.9 CL 1.27 7 High elevated river terraces 0e30 3 7.6 CL 1.27 30e60 2.2 7.7 CL 1.27 8 Low elevated sand sheet 0e30 1.9 8.3 LS 1.36 30e60 1.35 8.4 LS 1.52 9 High elevated river terraces 0e25 3.1 8.1 C 1.26 25e80 3.8 8.1 C 1.29 10 Low elevated river terraces 0e30 5.4 8.1 C 1.26 30e100 5.9 8.1 C 1.24 11 River levee 0e35 3.9 8.1 C 1.28 35e90 3.8 8.1 C 1.31 12 Overflow basin 0e25 2.1 7.4 SCL 1.39 25e70 3.2 7.5 SL 1.37 13 Decantation basin 0e35 7.4 8.2 C 1.22 35e80 6.8 8.1 C 1.24 14 Sandy beach 0e30 6.1 8.4 S 1.32 30e75 3.2 8.5 S 1.33 15 Overflow mantle 0e30 2.3 8.5 C 1.26 30e80 1.4 8.6 C 1.21 16 Low elevated sand sheet 0e25 4.2 7.9 S 1.58 25e60 6.2 7.9 S 1.57 17 High elevated sand sheet 0e20 11.4 7.6 S 1.65 20e85 20.6 7.7 S 1.6 18 Hammock 0e30 1.8 7.9 S 1.54 30e70 2.3 8.0 S 1.6

Note: C ¼ Clay, SCL ¼ Sandy clay loam, SL ¼ Sandy loam, S ¼ Sandy, LS ¼ Loamy sand. 186 egyptian journal of basic and applied sciences 2 (2015) 183e189

Table 3 e Summary statistics of some soil properties. Soil Depth Top soil (0e30 cm) Subsoil (30e60 cm) Parameters Mean Min. Max. Mean Min. Max. EC dS m 1 3.78 1.8 11.39 4.23 1.35 20.59 Bulk density g/cm3 1.34 1.22 1.65 1.35 1.21 1.60 pH 8.06 7.4 8.63 8.07 7.5 8.7

wetlands and hammock. The landforms of fish ponds and water bodies of the lacustrine plain dominate the north- eastern parts of the governorate.

3.2. Spatial distribution of soil properties Fig. 4 e Spatial distribution of bulk density in the surface 3.2.1. Surface soil layer soil layer. Table 2 represents some physical and chemical analyses of the soils in the different landform units and Table 3 represents summary statistics of some soil properties. In this study, the distribution of EC and Fig. 4 represents the spatial distribution data indicated that the soil texture was clayey to sandy; the of bulk density in the topsoil layers over the study area. fine texture attributed the flood plain. Values of soil pH were slightly alkaline, ranging between 7.4 and 8.63 in the different 3.2.2. Subsurface soil layer soils; the highest value characterized the overflow basin. The The data indicated that the soil texture was clayey to sandy; average pH value in the surface layers was 8.06. The spatial the fine texture attributed the flood plain. Values of soil pH distribution of EC in the study area indicated that the EC were slightly alkaline, ranging between 7.5 and 8.7 in the values ranged from 1.8 to 11.39 (dS/m) in the surface layer. The different soils; the lowest value characterized the overflow average EC value in the surface layers was 3.78(dS/m). The basin. The average pH value in the subsurface layers was 8.07. highest value dominated the topsoils of high elevated sand The spatial distribution of EC in the study area indicated that sheet. The high values of EC may be attributed to the origin of the EC values ranged from 1.35 to 20.58 (dS/m) in the subsur- parent material and as a result of high water table [15]. Ac- face layer. The results showed that the lowest value of soil EC cording to FAI [26], the soils with EC value of below 0.80 (dS/m) (1.35) was in low elevated sand sheet, while the highest one are considered normal and suitable for all crop types. The (20.58) was observed in the high elevated sand sheet. The spatial distribution of bulk density (BD) showed that the BD average EC value in the subsurface layers was 4.23(dS/m). This values ranged from 1.22 to 1.65 (g/cm3); the highest value is in an agreement with Berhe et al. [31] who found that the occupying the surface layers of high elevated sand sheet. The average EC value in the subsurface layers was higher than the average BD value in the surface layers was 1.34(g/cm3). The average EC value in the surface layers. The high values of EC high values of bulk density may be due to the effect of using may be attributed to over-irrigation and other forms of poor heavy machinery on the surface layer [27,28]. These results agricultural and soil management practices [32]. The spatial are similar to those of other relevant studies [e.g. [15,29,30]] distribution of bulk density (BD) showed that the BD values who studied the spatial distribution of soil properties in soils north of the . Fig. 3 represents the spatial

Fig. 5 e Spatial distribution of EC in the subsurface soil Fig. 3 e Spatial distribution of EC in the surface soil layer. layer. egyptian journal of basic and applied sciences 2 (2015) 183e189 187

Fig. 6 e Spatial distribution of bulk density in the Fig. 7 e Classes of soil salinity risk in the surface soil layer. subsurface soil layer.

ranged from 1.21 to 1.60 (g/cm3); the high values occupying the second type occurs where human activities lead to an increase subsurface layers of hammock and the high elevated sand in evapo-transpiration of soil moisture in areas of high salt sheet. The average BD value in the subsurface layers was containing parent materials or with saline ground water [35].A 1.35(g/cm3). Similar results were obtained by Singh et al. [33] similar finding was obtained by El-Nahry [36], who found that who found that the average of BD values in the subsurface the main types of land degradation identified in an area layers was higher than the average BD values in the surface located between northern Isamillia and southern layers. The increase in bulk density with depth is due to Governorates were salinity and compaction as a result of migration of silt and clay from upper layers to this layer, human activities, inadequate soil management, using heavy which resulted in firm packing (consolidation) of soil [34]. machinery and human intervention in natural drainage sys- Fig. 5 represents the spatial distribution of EC and Fig. 6 rep- tems. Fig. 7 represents classes of soil salinity risk in the sur- resents the spatial distribution of bulk density in the subsur- face soil layer and Fig. 8 represents classes of soil compaction face layers over the study area. risk in the surface soil layers of the study area.

3.3.2. Subsurface layer 3.3. Classes of soil degradation risk Table 5 represents types, classes and areas of degradation risk affected subsurface soil layers of the study area. The obtained 3.3.1. Surface layer data revealed that the subsurface soils were subjected to a Table 4 represents types, classes and areas of degradation risk moderate to high risk of physical degradation (soil compac- affected the surface soil layer. The obtained data revealed that tion) and a low to very high risk of chemical degradation the soils had a moderate to very high risk of soil compaction (salinization). The high risk of physical degradation (soil and low to high risk of salinity. The high risk of soil compac- compaction) and chemical degradation (salinization) covered tion and salinity covered an area of 86.02 km2 (12.83%) and an area of 127.8 km2 (19.06%) and 10.6 km2 (1.58%), 2.28 km2 (0.34%), respectively. Human-induced salinization can result from two causes: poor management of irrigation schemes, and high salt content of the irrigation water or too little attention given to the drainage of irrigated fields. A

Table 4 e Types, classes and areas of degradation risk affected the surface soil layer. Type Risk class Area (Km2) Area (%)

Salinization Low 467.34 69.70 Moderate 200.88 29.96 High 2.28 0.34 Very high ee Compaction Low ee Moderate 584.47 87.17 High 85.35 12,73 Very high 0.67 0.1 Fig. 8 e Classes of soil compaction risk in the surface soil Total 670.5 100 layer. 188 egyptian journal of basic and applied sciences 2 (2015) 183e189

of soil compaction risk in the subsurface soil layers of the Table 5 e Types, classes and areas of degradation risk study area. affected the subsurface soil layer. Type Risk class Area (Km2) Area (%) Salinization Low 474.85 70.82 4. Conclusion and recommendations Moderate 185.06 27.60 High 9.39 1.4 Understanding the spatial distribution of soil properties and Very high 1.2 0.18 their relation with the landforms is the key to setting the Compaction Low ee Moderate 542.7 80.94 appropriate land management. Distribution of the soil prop- High 127.8 19.06 erties over the landforms of Damietta governorate had been Very high eeinvestigated by using spatial analyses techniques.The area Total 670.5 100 includes various landforms i.e. flood plain, lacustrine plain and marine plain. The distribution of the soil properties i.e. EC and bulk density (BD) represented a wide variation over these respectively. Same results were obtained by Wahab et al. [29] landforms. It can be concluded that a significant area in the who found that the human induced land degradation hazards governorate is subjected to a high risk of soil compaction and due to soil compaction and salinization was slight to high in salinity. Moreover, processes of compaction and salinization soils north of Nile Delta. Fig. 9 represent classes of soil salinity changes from low to high in different land units. GIS is very risk in the subsurface soil layers and Fig. 10 represent classes helpful tool to store, manipulate and quantitatively evaluate soil degradation. In addition, the following recommendations suggested for reducing land degradation in the city:

Establish methods to remedy any degraded land prior to agricultural or residential use (i.e. salinity, erosion, leech- ing, stagnation, chemical composition, etc.). Reducing soil compaction could be realized through avoiding field practices that have the potential to damage the soil structure. So, conducting field operations with heavy machines on wet soils should be minimized. Governments should form committees to promote sus- tainable land use practices. Introduce the concept of a controlled environmental greenhouse as an option/alternative to farms whose land easily suffers from land degradation. Revert to such agricultural practices as crop rotation in Fig. 9 e Classes of salinity risk in the subsurface soil layer. order to preserve soil quality. Move to drip irrigation methods to maintain soil quality. Use minimum/conservation tillage methods. Use precision agricultural methods. Promoting land-use systems that provide permanent vegetative cover to protect the soil, increase fertility and optimize water penetration. Identifying the causes of land degradation before pre- scribing solutions for it. Before developing land, a clear evaluation procedure should be established and implemented. The government should pass legislation that protects land against practices that lead to degradation. Establish community environmental awareness programs. Decisions regarding land use should be based on continual research and monitoring on the condition and stability of the land. Informational meetings regarding the impact of land use on the environment should be held periodically within the community Educate the people about respecting the land and use of sustainable land practices. Fig. 10 e Classes of compaction risk in the subsurface soil Using techniques that provide economic benefits for land layer. users in the short as well as the long term. egyptian journal of basic and applied sciences 2 (2015) 183e189 189

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