IJERD – International Journal of Environmental and Rural Development (2021) 12-1

Research article
erd

Rainwater Harvesting as a Mean for Water Conservation inOvche Pole Region, Macedonia
OGNEN ONCHEVSKI
Graduate School of Agriculture, Tokyo University of Agriculture, Japan
Email: ognenoncevski@hotmail.com

MACHITO MIHARA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan
Email: m-mihara@nodai.ac.jp
Received 30 December 2020

Accepted 30 June 2021(*Corresponding Author)

Abstract Ovche Pole is an area in Macedonia located in the central part of the country. The
region is the second largest grain producing area and agriculture is the main economic activity
for most of the people there. From an agro-ecological perspective, larger part of the region ispart of the sub-humid agricultural zone; however, there is an area that is identified as semiarid
agricultural zone, too. In both agro-ecological zones, main problem and constraint for
agricultural production are the dryness and low precipitation in the growing period. This
problem is especially emphasized on the agricultural land without irrigation system. Therefore,
this study analyzes rainwater harvesting approach as a mean for water conservation andimprovement of agriculture productivity in the research area. The first objective of this study isto determine the runoff potential in the research area and the second is to identify suitable areas
and measures for water harvesting. Remote sensing and geographic information systemtechniques were used to obtain, prepare and analyze input data. Because of simplicity and lackof hydrological data in the research area, SCS-Curve Number method was used for rainfallrunoff modelling. Hydrologic Soil Group (HSG) map was build using data obtained from theMacedonian Soil Information System (MASIS). Land use/land cover was prepared by
combining supervised classification of Sentinel-2 satellite image and visual interpretation andediting to improve the classification. Slope map was generated from a 20-meter resolution
DEM data obtained from the Agency for Real Estate Cadaster. Data of the annual average
precipitation for the period between 1981 and 2010 was obtained from the National
Hydrometeorological Service. Set of rainwater harvesting measures were selected as
appropriate for the context of the research area. The site suitability for each rainwater
harvesting intervention was determined by considering different varying parameters like runoff
potential, slope, soil texture, land use, stream order of proximity to users. The results indicatethat rainwater harvesting can be considered as a strategy for water conservation in the research
area.
Keywords water conservation, rainwater harvesting, surface runoff, SCS-SN method,
suitable site selection

INTRODUCTION
Having in mind the United Nation Convention for Combating Desertification (UNCCD) definition,
approximately 40% of the global land can be considered as a type of dryland (WRI, 2012). Although
there are many challenges, in these areas water is the key limiting constraint for agricultural andbiological productivity. Irrigated areas to some extent can avoid this constraint, however rainfed
agricultural land is dependent on water that comes as precipitation. To unlock the potential of smallⒸ ISERD95

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scale rained agriculture, investments in better water management need to be emphasized. In dry area
water harvesting coupled with in situ water management as well as improved soil, nutrient and crop
management have great potential. In humid areas, in situ water management technologies such asconservation agriculture based on no-till, mulching and crop rotation are generally more suitable andappropriate. Mekdaschi and Liniger (2013) define water harvesting (WH) as “The collection andmanagement of flood water or rainwater runoff to increase water availability for domestic andagricultural use as well as ecosystem sustenance”. Although there are multiple benefits, there are someconsiderations that must be taken before water harvesting systems can be successful implemented.
Therefore, objectives of this study is to determine the runoff potential in the research area and to identify
suitable areas and measures for water harvesting. In this line different methodologies and criteria for WH
site and method selection were developed, however two main groups are defined-biophysical andsocio-economic (Ammar et al., 2016). In his study Ammar (2016) identified three commonly most
followed set of criteria for selection of suitable WH. Those are the sets proposed by: Integrated
Mission for Sustainable Development (IMSD) in 1995, Dr. Theib Y. Owesi in 1998 and Food andAgriculture Organization of the United Nations (FAO) proposed in 2003. Since field surveying can beresource consuming, nowadays the assessment and selection of suitable WH sites and measures isassisted by remote sensing and geographical information systems, because when coupled they are costefficient and provide reasonably good possibility for analyzation of spatial data (Wani et al., 2009)
METHODOLOGY
Description of the Study Area
Ovche Pole is a plain located in central
part of Macedonia that takes an area of649 km2. It lies between latitude 41 59
30 N and 41 38 43 N and longitude 21
48 13 E and 22 01 28 E (Fig. 1).
Agriculture is dominant economic
activity in the region. Agricultural landtakes 40,183 ha (62% of the study area),
however much of the arable land is not
irrigated. Forests cover 14,619 ha(22.5%) of which 2/3 are degraded,
whereas 9,134 ha (14%) are pastures(CORINE LC/LU, 2012). The climate
is modified warm continental with
Mediterranean influence (Zikov, 1995;
Filipovski et al., 1996). Considering theFig. 1 Geographical position of the research area
data between 1981 and 2010 the annual
average precipitation in the region is455 mm. From an agro-ecological perspective, larger area of the region is part of the sub-humid
agricultural zone; however, there is an area that is identified as semiarid agricultural zone, too. In bothagro-ecological zones, main problem and constraint for agriculture production are the dryness and low
precipitation in the growing period (Aksoy et al, 2020).
MaterialsⒸ ISERD

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Different data such as land use/cover data, Sentinel-2 satellite images, elevation model (DEM), climate
data and soil data were used in this study analysis. Land cover/land use (LCLU) analysis was done byusing CORINE Land Cover (CLC2018) data set from 2018, program coordinated by European
Environmental Agency (EEA) and Sentinel-2 satellite image. Soil data were obtained from The
Macedonian Soil Information System (MASIS). Watershed delineation, stream network, slope,
topographic maps were generated using 20-meter resolution DEM obtained from the Agency for Real
Estate Cadaster. Average year precipitation of 455 mm. was derived from climatic data for the period
between 1981 and 2010 provided by the National Hydrometeorological Service (NHS).
Methods
Assessment of the water harvesting potential and identification of suitable water harvesting sites wasdone by evaluation of parameters such as: surface runoff, land use/cover, slope, soil infiltration
characteristics, stream order and proximity to users. The complete quantitative and qualitative data
analysis in this research was done by remote sensing and Geographical Information System (GIS)
techniques. To compute hydrological elements more accurately generation of Land Cover/Land Use
map is required (Rana and Suryanarayana. 2020). In this study CORINE Land Cover 2018(CLC2018)
dataset for Macedonia together with Sentinel-2 satellite image were combined to create the LCLU map
for the research area. The Sentinel-2 image captured on 20 August 2019 was used as a backgroundinformation for additional interpretation and editing of existing CLC2018 vector layer. We only used
the bands with 10-meter resolution (blue B2:490 nm, green B3:560 nm, red B4:665 nm, NIR B8:842
nm). As a result of this hybrid process, a new more precise and detailed land cover map was created.
For the Hydrological Soil Group (HSG) analysis and map generation three raster files on sand, silt andclay content in soil were used. Each pixel is specified with a 100 meters resolution and a value that
represents the content of specific soil fraction expressed in unit percent. Using raster calculator andreclassification function in ArcGIS Pro, the three layers were used to create new raster layer. In thisraster each pixel was assigned a value that represented some soil texture class, following the USDA
textural soil classification. Considering the infiltration rate of various soil texture each pixel wasreclassified into A, B, C or D hydrologic soil group. Accordingly, the hydrologic soil group (HSG)
map was prepared for the entire research area. The DEM data was used to generate the slope map andstream network map for the research area. Surface runoff is the primary component of every water
harvesting system. In this study Conservation Service Curve Number (SCS-CN) methodology wasused to calculate the runoff depth and generate run-off potential map for the research area. The SCS
run-off equation is widely used in estimating direct run-off because of its simplicity, flexibility andversatility (Kumar and Jharya. 2016) and often used by researcher for watersheds that are ungauged, as
it is the study area in this research. Although the method is designed for a single storm, it can be scaled
to calculate the annual values for run-off of an area. Basically, the SCS-CN method depends on therelationship between the rainfall parameter (P) and the run-off depth (Q), simplified into the CN
concept. The CN is a dimensionless run-off index determined based on Hydrological Soil Group(HSG), land use/land cover and Antecedent Moisture Conditions (AMC). The CN method can also
reflect the effect of changes in land use on run-off. The CN values range between 1 and 100. Highervalues of CN indicate higher run-off. In this study the runoff derived by SCS-CN method wasexpressed as runoff coefficient which represent the ratio between the runoff and rainfall. Based on therunoff coefficient a runoff-potential map was created in which the run-off coefficient is reclassified infour classes: low run-off potential, moderate run-off potential, high run-off potential and very high runoff potential.
Rainwater Harvesting Measures Selection and Site Suitability AnalysisⒸ ISERD

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The rainfall, geology, physiographic, land use, climatic conditions and social set-up are the basic
factors to be understood by the rainwater harvesters to choose the proper technique of rainwater
management in a particular set-up identified by them. As first step in process, a set of RWH measures
were identified and selected; in the second step, for each measure a set of site selection suitability
criteria were compiled; and as last step, RWH site suitability analysis was performed. Selection ofsuitable RWH measures was done by revieing studies, manuals and other on-topic literature. We
identified to groups of measures. First group are measures that can be implemented in valley
formations such as impermanent water streams and gullies, such as: ponds, gabion checks, boulder
checks and brushwood checks. Second group of measures are those that can be implemented on theridge formations. Here we identified revegetation, contour ditches and contour bunds as possible
appropriate measure. In the second step, we complied criteria for suitable site selection for each of theidentified measure in the first step. The criteria for water harvesting site selection related to each water
harvesting group of measure are presented in Table 1 and Table 2. According to the review study doneby Ammar et al. (2016) on identification of suitable sites for water storage in arid and semi-arid
regions, it was found out that the most common biophysical layers or criteria applied were slope
followed by land use/land cover and soil type. In this study we selected runoff, land use/land cover,
HSG, slope, stream network and distance to users play a critical role in rainwater harvesting site
selection. These thematic layers were used as input data for a series of operations done in ArcGIS Pro
that enabled identification of appropriate sites for each identified rainwater harvesting measure.

On-ridge
interventions

Table 1 Criteria for selection of on-ridge rainwater harvesting measures
Water harvesting
intervention

Runoffcoefficient

Slope (%)

Revegetation

>0.5

>25

Contour trenching>0.5

10 - 25

Contour bunds>0.50-10

Hydrology Soil
Group (HSG)

Land use

A, B, C, D

Land principally occupied byagriculture with significant areas ofnatural vegetation; Pastures,Grasslands; Sparsely vegetated areas;
Transitional woodland-shrubs

A, B, C, D
A, B, C, D

On-stream interventions

Table 2 Criteria for selection of on-stream rainwater harvesting measures
Water harvesting
intervention

Runoffcoefficient

Slope(%)

StreamOrder

Hydrology Soil
Group (HSG)

Distance to users

Irrigation ponds>0.50-5

1-2C, D< 250 meters fromagricultural land

Livestock ponds>0.50-51-2C, D< 1000 meters from livestockbarns

Gabion checks

>0.5

0-5

1-2(gullies)*

A, B, C, D

n/a

Boulder Checks>0.55 - 20

1-2

A, B, C, D

n/aBrushwood checks>0.5> 20

1-2

A, B, C, D

n/a

RESULTS AND DISSCUSIONRunoff PotentialⒸ ISERD

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The run-off potential of the area affects the recharge and movement of surface water and is one of theimportant parameters for rainwater harvesting. (Kumar and Jhariya, 2016). The run-off potential map(Fig. 2) was built based the SCS-CN method by integrating average annual rainfall for the period
between 1981 and 2010, land use/land cover information, and distribution hydraulic soil groups in theresearch area. The runoff derived by SCS-CN method is a function of runoff potential which can be
expressed in as runoff coefficient - ratio between the runoff and rainfall. To perform RWH site
suitability analysis the run-off potential was reclassified as very high run-off potential, high run-off
potential, moderate run-off potential and low run-off potential. Category description and distribution in
the research area is presented in Table 3. Results show that 26.8% of the total research area has very
high runoff potential and 66.8% has high runoff potential.
Table 3 Runoff coefficient category description and distribution
Runoff coefficient

Description

Surface area (km2)

Percent of total area (%)≤ 0.5 (0.00 – 0.5)

Low runoff potential

23.25

3.6

3.3

0.5

14.6

2.3

115.3

17.9

314.1

48.9

172.2

26.8

≤ 0.6 (0.51 – 0.6)
≤ 0.7 (0.61 – 0.7)

Moderate runoff potential≤ 0.8 (0.71 – 0.8)
≤ 0.9 (0.81 – 0.9)
≤ 1.0 (0.91 – 1.0)

High runoff potential
Very high runoff potential

Fig. 2 Runoff coefficient map of the research area
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Rainwater Harvesting Site Suitability Analysis
Rainwater harvesting site suitability analyses, based on the criteria given in Table 1 and Table 2
showed that identified measures can be applied on significant part of the research area. On-ridge
measures can be implemented on 59% of the total area. Detailed information for each on-ridge measure
is presented in Table 4, the distribution map is shown in Figure 4. Regarding the on-stream measuresdetailed analysis is presented in Table 5. and the distribution map in Figure 4. As an implementation
unit for ponds and gabion checks is the number of pond-structures that can be build, whereas forbrushwood and boulder check implementation unit is the length of stream sections appropriate forimplementation.
Table 4 On-ridge measure distribution analysis
On-ridge measures
Water harvesting intervention

Implementation area (km2)

Percent of total area (%)

Contour bunds

193

30

Contour trenches

109

17Re-vegetation

7712Fig. 3 On-ridge measures distribution mapⒸ ISERD

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Table 5 On-stream measure distribution analysis
On-stream measures
Water harvesting intervention

Implementation units

Irrigation ponds

43 ponds

Livestock ponds

11 ponds

Gabion checks

183 checks

Brushwood checks

91 km (stream length)

Boulder checks

297 km (stream length)

Fig. 4 On-stream measures distribution map
CONCLUTION
Ovche Pole region is part of the sub-humid and semiarid agricultural zone in Macedonia. Main
constraint for agriculture production is dryness and low precipitation amounts during the growing
season. This study explores the potential for implementation of rainwater harvesting measures as
strategy for water conservation. The results show that 93.6% of the total area has potential to generatehigh and very high runoff. Rainwater harvesting site suitability analysis done in the study implies thatⒸ ISERD101

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59% of the research area satisfy the criteria for implementation of the selected on-ridge RWH measures.
Analysis shows there are significant number of potential sites suitable for implementation of on-stream
RWH measures that can also significantly contribute to conservation of water resources in the research
area.
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European Union, Copernicus Land Monitoring Service. 2018. European Environment Agency (EEA).
Kumar, T. and Jhariya, D. 2016. Identification of rainwater harvesting sites using SCS-CN methodology, remotesensing and geographical information system techniques. Geocarto International, 32 (12), 1367-1388.
Mekdaschi S.R. and Liniger, H. 2013. Water harvesting: Guidelines to good practice. Centre for Development
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