Assessment model of water harvesting and storage location using GIS and remote sensing in Al-Qadisiyah, Iraq

Abstract

One of the important steps towards optimizing land productivity and water availability for the semi-arid and arid areas is the identification of potential sites for water harvesting. Therefore, this paper uses the Geographical Information System (GIS) techniques to select the optimized sites for water harvesting in Al-Qadisiyah Governorate, Iraq. Geographic water management capabilities are applied as a spatial analysis model. Data from global data repositories are retrieved followed by rescaling them to a spatial resolution to acquire a manageable input data set. The Soil Conservation Service Curve Number (SCS-CN) model is used to calculate the potential runoff as an intermediate input. Multi-Criteria Evaluation techniques are adopted to identify the relative importance and suitability levels of the input parameters set to manage the water supply. The suitability for identifying irrigation pond and dam location(s) was considered in this study. To achieve this goal, the criteria for eligibility for water harvesting areas have been completed on the basis of the conditions in the study methods. Based on the hydrological and geomorphological standards of the study area, suitable sites for harvest areas were identified and it was divided into four classes in terms of their suitability for water harvesting, namely very low, low, moderate, and high suitable for water harvesting. It can be concluded that the findings of this research can be used to assist in water resources management as an efficient planning tool to ensure sustainable development of the water in Iraq who suffers from water shortages.

An integrated new approach for optimizing rainwater harvesting system with dams site selection in the Dewana Watershed, Kurdistan Region, Iraq

“…According to FAO guidelines, population density plays a significant role in selecting suitable water harvesting sites [ 46 , 86 , 87 ]. The official Iraqi government documents and local authority indicate a total population of 105,000 people in the Dewana watershed [ 21 , 88 ].…”

Identifying Suitability Rainwater Harvesting Zones in Diyala Watershed, Iraq, Using Multi-Criteria Analysis and GIS Modelling

“…In the UK (southeast of England), optimum RWH sites were determined utilizing a GIS-based decision support system and remote sensing [12]. In Iraq (Maysan Province), suitable RWH sites were identified using a geographical information system-based Multi-Criteria Evaluation where Fuzzy Linear Membership was utilized to standardize the criteria and Fuzzy Overlay (GAMMA) for a combined of criteria [13], Also in Al-Qadisiyah Province, suitable RWH sites were selected using Geographical Information System techniques where Multi-Criteria Assessment technologies were used to find the comparative significance and appropriateness degrees for the input data, and the Soil Conservation Service Curve Number (SCS-CN) model was utilized to compute the possible runoff as an intermediary input [14]. According to the preponderance of similar research, using practicable methods and choosing appropriate factors are essential aspects in effectively executing geospatial and multi-criteria decision analysis ways in drawing maps of probable rainwater harvesting zones [15,16].…”

Characterization of the water bodies of Extremadura (SW Spain)

“…McDonald et al (2012) performed this kind of study in the USA, while Marín-Comitre et al (2021) surveyed easily identifiable small water bodies (SWBs) in Spain, accurately delineated from free aerial images using Geographic Information System (GIS) tools, by digitizing (WBs) and then extracting them as a layer on ARCGIS from an orthophoto, through using Extract By Mask tool. Estimating the storable water using GIS and remote sensing can be a feasible solution for small areas such as a single farm (< 1000 ha) or municipality (< 100 km 2 ) (Abijith et al, 2020;Al-Khuzaie et al, 2020;Duarte et al, 2014;Rashash & El-Nahry, 2015;. Technical limitations arise when the target of the study is a large land surface area such as, for instance, the region of Extremadura (41,634 km 2 ) (Terasmaa et al, 2019).…”