Visualizing sustainable rainwater harvesting: A case study of Karbala Province

Al Ibraheemi Abbas; Basim K. Nile; Waqed H. Hassan

doi:10.1515/eng-2024-0009

Article Open Access

Visualizing sustainable rainwater harvesting: A case study of Karbala Province

Al Ibraheemi Abbas , Basim K. Nile and Waqed H. Hassan

Published/Copyright: June 26, 2024

Published by

Become an author with De Gruyter Brill

Submit Manuscript Author Information

From the journal Open Engineering Volume 14 Issue 1

Abstract

The management of rainwater collection in a practical way is a fundamental need for the management of water resources in a manner that is sustainable. The goal of this research is to determine whether or not remote sensing technology is effective in providing data on precipitation for the purpose of locating rainwater collection tank locations in the province of Karbala. Rainfall patterns fluctuate considerably. Remote sensing may not capture variability enough to estimate the rainfall period and location. Sustainable rainfall harvesting requires accurate rainfall timing and distribution. This information is applied in the modeling of hydrological processes, the management of disasters, and environmental research. Following the completion of a geographical study, it has been established that the city of Karbala may be divided into two basic sections. Through the use of estimation, it is possible to more easily identify the region that is ideal for the location of rainwater-harvesting reservoirs and lakes. On the contrary, it is crucial to keep in mind that a location that was chosen based on average rainfall over a period of two years could not be suitable for other time periods. This is an idea that should be kept in mind several times. To put this into perspective, when choosing a location, it is vital to take into consideration the severity of the rainfall as well as the geographical location of the area. Particularly in locations such as Karbala, the implementation of data visualization systems into water management practices has the potential to improve both the efficiency and sustainability of water management methods. The findings of this study show the significance of implementing precise site selection techniques to enhance rainwater collection systems and encourage activities that are environmentally responsible for water management.

Keywords: data visualization; rainwater management; remote sensing; sustainable harvesting, sustainable watershed

1 Introduction

Recently, the sustainable rainwater collection area has seen notable progress due to the increasing acknowledgment of the significance of data-driven decision-making in enhancing rainwater harvesting (RWH) systems for long-term sustainability and socioeconomic advantages [1,2,3].

Data visualization in RWH systems is a crucial tool that provides simple and understandable representations to help understand complicated data patterns and support informed decision-making processes [4,5,6,7,8]. Stakeholders, including politicians, engineers, and community members, can analyze rainfall patterns, water storage capacities, water quality parameters, and system performance more clearly and precisely using visual representations like charts, graphs, and maps. This improved comprehension encourages cooperation in building and maintaining sustainable RWH systems, which enhances the efficient use of water resources [9,10]. This promotes joint efforts to construct and manage sustainable harvesting systems for rainwater.

Graphing data is crucial for the advancement of rainwater collection technology [5,11]. Visual representations of rainfall data help decision-makers identify patterns and trends, allowing them to make precise and timely decisions on RWH techniques and timing. Real-time monitoring and modeling improve water management efficiency by reducing hazards related to water surplus and maximizing the use of resources [7,12].

Information visualization can improve community involvement and understanding of sustainable rainwater gathering systems. Providing communities with easily understandable and significant data enables them to take an active role in overseeing their water resources. This promotes a feeling of ownership and accountability in activities such as rainwater collection, water conservation, and achieving sustainable objectives in the long run [8,13].

This research intends to enhance the field of data visualization in sustainable RWH by offering a case study on the Karbala province. We aim to use data visualization, remote sensing technologies, and geographical analysis to find the best locations for RWH equipment. This will improve water resource management in the area. Our research seeks to fill current gaps in the field and offer insights to guide decision-making for promoting sustainable water management methods in Karbala and other areas.

Remote sensing uses satellite or aerial photos to measure rainfall. This data’s accuracy and resolution can vary, affecting regional precipitation predictions. Accurate sustainable rainfall harvesting (SRWH) system construction and operation require high-resolution data.

2 Literature review

In this century, sustainable RWH has gained popularity as an instrument to tackle water scarcity and boost environmental sustainability [7,13–16]. Visualizing data becomes essential for improving decision-making and controlling RWH systems since there is a growing desire for environmentally friendly water resource management [17,18]. This literature review discusses data visualization in sustainable RWH, covering its advantages and disadvantages [12,19].

2.1 RWH and sustainability

The methodology of RWH has been widely employed for an extended period of time. It includes harvesting and storing rainwater for numerous purposes, including irrigation, residential consumption, and resupplying groundwater resources [8,15,20]. The strategy mentioned previously is considered sustainable since it has the ability to reduce reliance on traditional water sources, prevent runoff, and reduce the effects of crises and shortages of water [5,21,22].

2.2 RWH visualization in scientific research

The Environmental Systems Research Institute (Esri ArcGIS) is essential for remote precipitation analysis and visualization. Researchers in meteorology, hydrology, environmental science, and related domains need this technology. For research, strategic planning, and informed decision-making, these people demand precise and up-to-date rainfall data. With academic integrity, the developers may investigate ArcGIS’s comprehensive and sophisticated functions in remote precipitation data analysis [17,18,23–27].

A number of those assessed throughout the research project took advantage of the opportunity to investigate rainfall data through the application of diverse remote sensing technologies. Table 1 provides a detailed review of the studies, effectively highlighting their primary outcomes and corresponding recommendations [6,7,10,23–37]. Taking advantage of data visualization has a major significance in the framework of sustainable water harvesting, as it serves to offer significant insights, facilitate informed decision-making processes, and foster efficient communication among various parties involved. There are several significant ways in which data visualization integrates with the sustainability of RWH [1,28].

Table 1

Review of some studies conducted on remote sensing visualization [23–36]

Authors	Main findings	Outcomes measured
Ya’acob et al. [23]	GIS mapping can be used to identify potential RWH sites in Peninsular Malaysia	Catchment area
	RWH can reduce the risk of storm water flooding in densely populated areas	Projected rainwater collection
	RWH can create green jobs in the solar field and reduce environmental impacts
Sayl et al. [25]	GIS and remote sensing can be used to identify suitable locations for RWH	Suitable location for RWH
	The proposed method is relatively supportive of analyzing geospatial data to determine and select the optimal site for RWH and minimize evaporation losses	Storage volume
	The total suitable area for water harvesting was 28% of the study area, while 21% indicated moderate suitability.	Surface area
Karani et al. [31]	A framework was proposed to optimize the site selection for reservoirs by intersecting various data points	Site selection for reservoirs
	The framework uses a three-step approach to combine stream networks, digital elevation, and soil quality to produce the most viable reservoir sites
	The method yields consistent results that the manual inferences made from the data under consideration can support
Baby et al. [27]	GIS was used to assess the total amount of water harvestable at the household level in Wollert, Victoria	Rooftop RWH potential
	Eucalypt Estate Wollert has a large potential for rooftop RWH, with an estimated 179.11 liters of water available per person per day throughout the year	Total amount of water harvestable at the household level
	RWH systems can provide water at or near the point of demand with few negative environmental impacts	Area of various types of roofs and their potential for planning
		Amount of water available per person per day
Choudhary et al. [34]	GIS and field survey techniques can be used to assess the RWH capacity of national highways	RWH capacity
	A 5-kilometer segment of National Highway 27 can store 65 million liters of water for 2000 villagers for 240 days	Amount of water that can be harnessed for future use
	RS and GIS provide a good opportunity to gain a better understanding of contour patterns and natural and manmade profiles	Number of villagers who can benefit from the harvested water duration of the harvested water
		Per capita consumption of water
Tiwari et al. [24]	A GIS-based methodology was developed to identify suitable locations for RWH structures in the semi-arid environment of the Khushkhera-Bhiwadi-Neemrana Investment Region (KBNIR) in the Alwar district of Rajasthan.	Locations suitable for RWH structures
	Seven locations were identified as suitable for RWH structures, with two locations being excellent, three locations being good (if provisions for overflow structures are made for them), and two locations being not suitable	RWH potential of the study area
	The total RWH potential of the study area is 54.49 million cubic meters, which is sufficient to meet the water requirements if harvested and conserved properly
Hari et al. [32]	The GIS technique can be used to assess the potential of RWH in a given area	Capacity of an individual catchment for harnessing rainwater
	GIS can be used to identify suitable types of water harvesting structures and the number of structures required	Total potential of water that can be harvested
	GIS can be used to calculate the areas of rooftops and roads for water harvesting	A suitable type of water harvesting structure
		Number of structures required
Ahmad [36]	Remote sensing and GIS can be used to identify suitable sites for RWH	Site suitability for RWH
	The north, south-western, and middle parts of the study area are suitable for RWH
	Weighted overlay analyses in a GIS environment can be used to identify different criteria for site suitability
Chiu et al. [35]	The GIS-simulation-based design system GSBDS proposed a cost-effective and feasible solution for designing RWHSs in urban areas to conserve both water and energy	Domestic water use savings
	RWHSs can facilitate 21.6% domestic water-use savings and 138.6 kWh/year-family energy savings	Energy savings (measured in kwh/year Family)
	The cost per unit of energy- savings is lower than that from solar PV systems in 85% of the RWHS settings	Cost of per UNIT energy saving
Gaikwad [33]	Remote sensing (RS) and GIS can be used to identify potential sites for RWH	Identification and mapping of impervious surfaces
	Terrain analysis, A DEM, hill shade, aspect direction of flow of streams, stream network, and stream ordering are features considered for hydromorphological analysis	Roof top areas as potential sites for water harvesting
	The water requirements of domestic and livestock, as well as crop requirements, can be estimated from daily demand and evapotranspiration (ET) crops	Hydro morphological Analysis of the Region
		Estimation of water resource up to village
Sayl et al. [25]	GIS and remote sensing can be used to identify suitable locations for RWH	Suitable location for RWH
	The proposed method is relatively supportive of analyzing geospatial data to determine and select the optimal site for RWH and minimize evaporation losses	Storage volume
	The total suitable area for water harvesting was 28% of the study area, while 21% indicated moderate suitability	Surface area
He et al. [38]	The passive atmospheric water collection study employing an ancient Chinese ink slab rediscovered MengxiBitan’s approach. A new method, this ancient Chinese ink slab collected airborne water when blown upon. This paper discusses the history and future of this technology in architectural engineering and other fields	Passive atmospheric water collection was tested on an antique Chinese ink slab. These materials passively collect fresh atmospheric water for interior and exterior buildings, according to the study. Temperature, air velocity, and low-frequency aspects evaluate water-self-sufficient ink slabs

2.3 Utilizing data visualization for sustainable RWH in Karbala

The practice of sustainable RWH has gained significant traction in recent years as a crucial solution to address water scarcity and enhance environmental sustainability [7,13–15]. In tandem with this trend, the importance of data visualization has emerged as a critical component in optimizing decision-making processes and controlling RWH systems, driven by the increasing demand for environmentally friendly water resource management [12]. While existing literature discusses the role of data visualization in sustainable RWH, this study aims to contribute to the field by addressing key gaps and presenting novel methodologies tailored to the context of Karbala province. Specifically, we highlight the distinctive features of our research compared to prior studies in the following ways:

Focused application in Karbala province: Previous studies have provided insights into RWH practices and visualization techniques in various regions. However, our study specifically targets Karbala province, recognizing the unique geographic and climatic characteristics of the area. By narrowing our focus, we aim to provide contextually relevant solutions that cater to the specific needs and challenges of Karbala.
Integration of remote sensing and Geographic Information Systems (GIS): While remote sensing and GIS technologies have been utilized in prior research to assess RWH potential, our study seeks to advance this integration further. We employ sophisticated methodologies to analyze remote precipitation data and visualize rainfall patterns with greater precision and detail. By leveraging these advanced technologies, we aim to enhance the accuracy and effectiveness of RWH site selection in Karbala.
Emphasis on data visualization: While previous studies acknowledge the importance of data visualization, our research places a stronger emphasis on this aspect. We not only visualize rainfall data but also analyze its implications for RWH system design and management. Through comprehensive visualizations, decision-makers can gain valuable insights into rainfall patterns and make informed choices regarding site selection and system optimization.
Quantitative assessment of rainfall patterns: In contrast to some prior studies that primarily focus on qualitative assessments, our research includes quantitative analysis of rainfall patterns spanning a 19-year timeframe. By providing specific and quantitative results, we offer a deeper understanding of the variability and intensity of rainfall in Karbala, enabling more precise decision-making in RWH system planning and implementation.

This study attempts to address gaps in the literature by providing a thorough and contextually appropriate investigation of RWH practices in the Karbala region. Through our research, we aim to offer practical insights and approaches that help develop sustainable water management practices in the region and beyond.

3 Materials and methods

Remote sensing and GIS are key for examining precipitation data for hydrological modeling, disaster management, and environmental research. ArcGIS a ways rainfall data analysis materials and methods will be discussed in this part. This research employs a combination of remote sensing technology and GIS to analyze precipitation data for the purposes of hydrological modeling, disaster management, and environmental research. The study is designed to assess the effectiveness of rainfall data analysis in determining suitable locations for RWH systems in Karbala province, Iraq. The study is conducted as demonstrated in Figure 1.

Figure 1

Study performed guidelines.

3.1 Rainfall data sources

Acquire historical and current precipitation data from credible institutions such as meteorological agencies, academic establishments, or satellite-based platforms such as NASA’s Tropical Rainfall Measuring Mission, the Center for Hydrometeorology and Remote Sensing (CHRS) of the University of California, Irvine, and the European Space Agency’s Climate Change Initiative. In this study, data were obtained from the CHRS data base for different time intervals starting from 2003 until 2021 for a specific region in Iraq, i.e., Karbala province.

Obtain relevant GIS layers, such as digital elevation models (DEM), land cover data, and hydrological layers, which are essential to performing rainfall data analysis. DEM layer was obtained from the United States Geological Survey (USGS), which represents the digital elevation of the Karbala study area.

3.2 Data preparation

This process involves the examination and cleansing of the rainfall data to identify irregularities, missing values, or unusual events. The ArcGIS Data Management tools could be employed to effectively cleanse and verify the integrity of collected data. The ArcMap toolbox can be used to repair gaps and missing data through the implementation of the “fill” command.

3.3 Data processing

Visualization is crucial to effective water harvesting, especially in dehydrated regions. RWH is essential for irrigation, drinkable water supply, and industrial operations. Many data processing and visualization methods may be used to sustain and improve this technique. The idea is to create prediction models that leverage historical data to attempt to forecast possible water availability and patterns of rainfall. Employ visual representations of these prognostications to promote strategic, enduring planning for the sake of sustainable water collection.

3.4 Preparation of hydrology parameters

The first phase requires performing a computation of flow direction based on the DEM raster image obtained from the USGS library (Figure 2). Subsequently, flow accumulation is determined using the resulting flow direction raster image in Figure 3. Finally, the basin, which represents the catchment area of the selected study area, will be generated in Figure 4.

Figure 2

DEM Karbala province.

Figure 3

Flow lines Karbala province.

Figure 4

Catchment areas of Karbala city.

3.5 Rainfall data collection

Remote rainfall data investigation begins with reliable data. Users may access satellite imagery, meteorological stations, and precipitation models in ArcGIS. Open-source platforms or governmental meteorological data collection organizations could supply this data. Data integrity and accuracy from reliable sources are absolutely essential. In this article, data regarding rain falls is obtained from the CHRS library, which is presented in Figure 5. It is assumed that the rainfall data collected from remote sensing technology, like imagery taken by satellites. It has an acceptable level of accuracy.

Figure 5

Precipitation data averaged over a wide range of years [2,5,18].

3.6 Data analysis

Rainfall data analysis includes visualization to improve water collection. Predictive models use historical data to forecast water supply and rainfall. To determine rainwater collection system locations, climate, geography, and hydrology are considered. Simulations of rainfall intensity assist select locations by assessing 5- and 19-year data variations. The analysis shows that rainfall intensity and location must be considered when choosing a site for rainwater collection systems to be effective and durable. This method addresses sustainable RWH system concerns using remote sensing, GIS analysis, and data visualization. In places with water scarcity and unpredictable precipitation, it improves controlling water supplies. Several essential criteria, including geography, hydrology, and rainfall intensity, have been selected for investigation due to their direct impact on rainwater availability and collection potential.

4 SRWH system challenges

The challenges associated with the implementation of SRWH systems through the utilization of remote sensing technology are varied and complex. The issues derive from the complicated characteristics of rainfall patterns, the constraints of remote sensing technologies, and the necessity for precise and reliable information to facilitate the design and administration of SRWH systems [26,31,34]. The following are a few significant challenges:

Data accuracy and resolution: Remote sensing captures rainfall data using satellite or aerial images. This data’s accuracy and resolution can fluctuate, rendering regional precipitation estimates inaccurate. To build and run SRWH systems accurately, high-resolution data are essential [36].
Time frame and territorial variability: Rainfall patterns fluctuate remarkably. Remote sensing could fail to capture variability adequately for an accurate estimation of rainfall temporal and geographical distribution. SRWH systems need precise rainfall timing and distribution data [32].
Cloud cover and interference: can block satellite photography, limiting real-time rainfall measurements. This phenomenon might be particularly difficult in cloudy or rainy places when precise data is required [26]. Furthermore, stream lines are visualized in Figure 2 to clarify the vision about the possibility of developing these streams into natural canals to serve a sustainable harvesting system [23].
Climate change: patterns of precipitation could shift, making historical statistics unreliable for planning. Adapting SRWH systems to changing climates and anticipating rainfall patterns is challenging [2].
Infrastructure and maintenance: SRWH systems required infrastructure and management. These systems must have periodic inspection of physical infrastructure including rainwater tanks or ponds. In certain places, building and sustaining these infrastructures becomes challenging [39].

5 Sustainable harvesting infrastructure site selection designation

Sustainable RWH implies an integrated strategy that prioritizes modifying harvesting systems according to rainfall intensity. This sustainable strategy became a greater hit as a sustainable solution to limited water availability, meeting urban and rural water needs [28].

Selecting an optimal site is the foundation of this technique. The selection of suitable sites is important for the performance of the RWH system. A detailed analysis of regional climate, terrain, and hydrology identifies the best rainwater collection system locations [23,28].

Reliable collecting systems are essential in locations with high rainfall variability. These systems could modify storage and drainage depending on rainfall intensity and frequency. During intense precipitation, the system must quickly accumulate and retain excess water to prevent flooding and erosion. However, during low precipitation, the system must efficiently use conserved water resources to ensure a steady supply for agriculture, sanitation, and household use [23,27,28,36].

This research suggests an alteration in site selection for harvesting systems to incorporate a simulation of rainfall intensity. Considering the previously mentioned data viewpoints (2, 5, and 19), the data visualization indicates that the site selected for the development of the system could not be suitable for meeting the 5- and 19-year data. Therefore, throughout the site selection process, it is important to systematically consider both the intensity of rainfall and its geographical location.

In summary, the concept of sustainable rainwater collection is centered on the strategic alteration of collection systems to effectively manage fluctuations in rainfall intensity. Through employing an efficient method of site selection, designing adaptable infrastructure, incorporating traditional knowledge alongside modern technology, and fostering active community engagement, these initiatives can successfully tackle the issue of water scarcity while simultaneously advancing environmental sustainability and enhancing resilience in response to shifting climate patterns [29,36].

6 Results and discussion

Data visualization for sustainable harvesting of rainwater was the primary objective of the article. To accomplish this objective, SRWH system practices and challenges have been assessed. The study further investigated how potential data visualization could enhance performance. Our research findings are as follows.

6.1 Current SRWH practices

In this decade, awareness of SRWH as a way to solve the water crisis and generate a sustainable water supply is expanding. The examination of current SRWH systems reveals a significant reliance on conventional methods of monitoring and reporting. The above techniques include traditional measurements of precipitation and water storage areas. This study (SRWH) takes advantage of remote sensing integrated with GIS to explore the present state of RWH practices, emphasizing the visualization of data associated with rainwater catchment areas around Karbala province. The data deployed in this analysis are obtained from academic organizations that include the USGS and CHRS databases. Results reveal that Karbala province could be divided into two main regions based on topographical data. This visualization of data enables decision-makers to identify areas that are optimal for RWH and utilization within a sustainable framework. The collected rainwater can be employed for various purposes, including agriculture and potable water systems; established, suitable treatment techniques are utilized. Figure 1 illustrates a DEM of the entire research area, highlighting locations that could potentially serve as water storage areas due to their valley-like elevation. These areas could be successfully used as natural harvesting tanks with appropriate adjustments. The darker red portion corresponds to a lower percentage of water collection zones, whereas the dark blue regions indicate a higher concentration of water-accumulating zones within the studied area. Based on the presented visual information, it is possible to extrapolate and choose the best suitable area for constructing sustainable RWH tanks. A variety of colures in the intermediate regions signifies the accumulation of an average amount of precipitation. Furthermore, Figure 3 shows how streamlines can be visualized, which is an important step toward realizing the possibility of turning these streams into natural drainage channels that could support a long-term harvesting system. The basins or catchment areas in Figure 4 could be visualized by employing the previously mentioned information and figuring out the catchment area’s location based on identified geographic boundaries using GIS and the data that is accessible.

6.2 Rainfall visualization

Visualizing rainfall patterns with GIS helps substantially benefit precipitation evaluation, governance, and management. This technology assists decision-makers in numerous sectors to optimize resource allocation, disaster safety, and sustainable development by providing valuable information. The data obtained by the CHRS organization consists of the application of a four-by-four-kilometer grid to measure and record rainfall information. Consequently, it has been observed that the resulting visualizations exhibit pixel-like characteristics. Figure 5 illustrates visualized rainfall data for the case study region. This study specifically examines Karbala province, in contrast to previous research that typically covers a wider geographic area. The study provides detailed instances of data visualization for DEM, streamlines, and catchment areas, delivering practical insights that may not be readily available in more general studies. Analyzed rainfall data from 2003 to 2021 in Karbala offers detailed insights that have not been identified in more general research. The study provides useful findings. Concentrating on a particular area, Karbala province, offering specific instances of data visualization for SRWH applications, and examining regional precipitation trends during a set time period. The insights enhance current research and provide practical examples for incorporating data visualization into sustainable RWH installations.

This article shares a visualization of rainfall details regarding the city of Karbala, spanning from the year 2003 to 2021. The study includes a graph of the average rainfall across the 19-year time frame as well as the visualization of rainfall occurrences across 5- and 2-year intervals.

The locations labeled with dark blue indicate the highest volume of rainfall, while the regions labeled with dark red reflect the lowest volume of rainfall. The locations labeled with colors in between represent an average amount of rainfall.

7 Conclusions

In brief, this article emphasizes the significant importance of data visualization in the framework of sustainable RWH. Through the utilization of GIS and remote sensing methodologies, decision-makers are empowered to make well-informed decisions on the most advantageous sites for RWH systems. Moreover, the utilization of rainfall visualizations provides important observations that are valuable in the management of resources and for planning for potential disasters. The article suggests modifying harvesting system site selection to simulate rainfall. The data visualization indicates that the site for 2-year average rainfall when it was constructed was insufficient for 5- and 19-year data; thus, site selection depends on rainfall intensity and location. The integration of data visualization technologies into environmentally friendly and accountable water management techniques offers the potential to enhance efficiency and promote sustainability in regions such as Karbala and other similar areas.

7.1 Recommendations

1. The use of remote sensing techniques can be used in the construction and study of sustainable RWH tanks and lakes.

2. To achieve sustainable management of water resources, it is imperative to utilize previous and future data provided by worldwide organizations, particularly future data.

3. The plan is to compare rainfall data with graphical data and conduct appropriate statistical analysis to minimize variations throughout the planning and design phases.

Acknowledgments

We express our sincere gratitude to the University of Kerbala and the University of Warith Al-Anbiyaa for their invaluable support and collaboration, which have been instrumental in the realization of this research endeavor. Their commitment to fostering mutual cooperation has provided us with the opportunity to delve into the critical realm of sustainable RWH through the lens of data visualization, with a particular focus on Karbala province. Special thanks are extended to the respective faculties of civil engineering departments at both institutions, whose expertise and resources have greatly enriched our research process. Their dedication to academic excellence has been an inspiration throughout this journey. Furthermore, we acknowledge the guidance and mentorship provided by our esteemed colleagues, whose insights have significantly contributed to the refinement of this study. Their unwavering support has been a source of encouragement at every step. Lastly, we extend our appreciation to all those who have contributed to this work, directly or indirectly, and to the wider academic community for their ongoing commitment to advancing knowledge and fostering sustainable development.

Funding information: The authors state no funding involved.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript, consented to its submission to the journal, reviewed all the results, and approved the final version of the manuscript. AIA: conceptualization, methodology, investigation, writing, visualization, and software. BKN: conceptualization, writing – review and editing, and supervision. WHH: conceptualization, writing – review and editing, and supervision.
Conflict of interest: Authors state no conflict of interest.
Data availability statement: This study's datasets, measurements, and computational methods are available. If allowed, interested parties should contact [Al Ibraheemi Abbas] at [abbas.h.ali@s.uokerbala.edu]. We encourage more research and validation and promote transparency and repeatability.

References

[1] Zhou Q. A review of sustainable urban drainage systems considering the climate change and urbanization impacts. Water. 2014;6:976–92.10.3390/w6040976Search in Google Scholar

[2] Ward S, Butler D. Rainwater harvesting and social networks: visualising interactions for niche governance, resilience and sustainability. Water. 2016;8:526.10.3390/w8110526Search in Google Scholar

[3] Martínez-Acosta L, López-Lambraño ÁA, López-Ramos Á. Design criteria for planning the agricultural rainwater harvesting systems: a review. Appl Sci. 2019;9:5298.10.3390/app9245298Search in Google Scholar

[4] Rodríguez-Sinobas L, Zubelzu S, Perales-Momparler S, Canogar S. Techniques and criteria for sustainable urban stormwater management. The case study of Valdebebas (Madrid, Spain). J Clean Prod. 2018;172:402–16.10.1016/j.jclepro.2017.10.070Search in Google Scholar

[5] Mohsen KA, Nile BK, Hassan WH. Experimental work on improving the efficiency of storm networks using a new galley design filter bucket. IOP Conf Ser Mater Sci Eng. 2020;671(1):012094.10.1088/1757-899X/671/1/012094Search in Google Scholar

[6] Wadi WM, Nile BK, Hassan WH. Climate change effect on The South Iraq Stormwater Network. International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). IEEE; 2022.10.1109/HORA55278.2022.9799860Search in Google Scholar

[7] Hassan WH, Nile BK, Al-Masody BA. Climate change effect on storm drainage networks by storm water management model. Environ Eng Res. 2017;22(4):393–400.10.4491/eer.2017.036Search in Google Scholar

[8] Al-Khuzaie AH, Alyaseri IJ, Nile BK. Flood reduction using green infrastructure in stormwater sewer systems: A case study in Al-Samawa city. AIP Conference Proceedings. AIP Publishing; 2023.10.1063/5.0131325Search in Google Scholar

[9] Maurya SP, Singh PK, Ohri A, Singh RK. Identification of indicators for sustainable urban water development planning. Ecol Indic. 2020;108:105691.10.1016/j.ecolind.2019.105691Search in Google Scholar

[10] Nile BK, Hassan WH, Alshama GA. Analysis of the effect of climate change on rainfall intensity and expected flooding by using ANN and SWMM programs. ARPN J Eng Appl Sci. 2019;14(5):974–84.Search in Google Scholar

[11] de Sá Silva ACR, Bimbato AM, Balestieri JAP, Vilanova MRN. Exploring environmental, economic and social aspects of rainwater harvesting systems: A review. Sustain Cities Soc. 2022;76:103475.10.1016/j.scs.2021.103475Search in Google Scholar

[12] Roozbahani A, Behzadi P, Bavani AM. Analysis of performance criteria and sustainability index in urban stormwater systems under the impacts of climate change. J Clean Prod. 2020;271:122727.10.1016/j.jclepro.2020.122727Search in Google Scholar

[13] Teston A, Piccinini Scolaro T, Kuntz Maykot J, Ghisi E. Comprehensive environmental assessment of rainwater harvesting systems: a literature review. Water. 2022;14:2716.10.3390/w14172716Search in Google Scholar

[14] Silva ADd, Mendes R, Bello LAL, Farias ALA. Sustainability of rain water supply technologies: a methodology applied to Belém county islands. Rev Tecnologia e Sociedade. 2018;14:34. 10.3895/rts.v14n34.7839Search in Google Scholar

[15] AL-Hamami A, Nile K, BH, Al-Baidhani J. The effect of high intensities of rainfall on the operation of the combined sewage system in populated areas. Kerbala J Eng Sci. 2021;1(1):75–92.Search in Google Scholar

[16] Alamri SNHS, Nile BK, Zwain HM. Topographic effects on stormwater drainage under different rainfall intensities case study of Al-Najaf City. Kerbala J Eng Sci. 2021;1(2):191–201.Search in Google Scholar

[17] Dibs H, Jaber HS, Al-Ansari N. Multi-fusion algorithms for detecting land surface pattern changes using multi-high spatial resolution images and remote sensing analysis. Emerg Sci J. 2023;7(4):1215–31.10.28991/ESJ-2023-07-04-013Search in Google Scholar

[18] Dibs H, Ali AH, Al-Ansari N, Abed SA. Fusion Landsat-8 thermal TIRS and OLI datasets for superior monitoring and change detection using remote sensing. Emerg Sci J. 2023;7(2):428–4.10.28991/ESJ-2023-07-02-09Search in Google Scholar

[19] Cacal JC, Austria VCA, Taboada EB. Extreme event-based rainfall-runoff simulation utilizing GIS techniques in Irawan Watershed, Palawan, Philippines. Civ Eng J. 2023;9(1):220–32.10.28991/CEJ-2023-09-01-017Search in Google Scholar

[20] Rosly MH, Mohamad HM, Bolong N, Harith NSH. Relationship of rainfall intensity with slope stability. Civ Eng J. 2023;9:75–82.10.28991/CEJ-SP2023-09-06Search in Google Scholar

[21] Nayel M, Nile B, Al-Hamami H. Estimation of the floods that occur in the drainage network during the rainy season. J Eng Appl Sci. 2018;13:8178–87.Search in Google Scholar

[22] Majeed AR, Nile BK, Al-Baidhani JH. Selection of suitable PDF model and build of IDF curves for rainfall in Najaf city, Iraq. J Phys: Conf Ser. 2021;1973(1):012184.10.1088/1742-6596/1973/1/012184Search in Google Scholar

[23] Ya’acob ME, Zulkifli SA, Zulkifli N, Iskandar AN, Othman MH, Zaidi MLA. GIS mapping for rainwater harvesting in ground-mounted large scale solar PV farms. 2022 IEEE International Conference in Power Engineering Application (ICPEA); 2022. p. 1–6.10.1109/ICPEA53519.2022.9744708Search in Google Scholar

[24] Tiwari KP, Goyal R, Sarkar A. GIS-based methodology for identification of suitable locations for rainwater harvesting structures. Water Resour Manag. 2018;32:1811–25.10.1007/s11269-018-1905-9Search in Google Scholar

[25] Sayl KN, Mohammed AS, Ahmed AD. GIS-based approach for rainwater harvesting site selection. IOP Conference Series: Materials Science and Engineering; 2020. p. 737.10.1088/1757-899X/737/1/012246Search in Google Scholar

[26] Chiu Y-R, Liaw C-H, Hu C-Y, Tsai Y-L, Chang H-H. Applying GIS-based rainwater harvesting design system in the water-energy conservation scheme for large cities. 2009 13th International Conference on Computer Supported Cooperative Work in Design; 2009. p. 722–7.10.1109/CSCWD.2009.4968144Search in Google Scholar

[27] Baby SN, Arrowsmith C, Al‐Ansari N. Application of GIS for mapping rainwater-harvesting potential: case study wollert. Vic Eng. 2019.10.4236/eng.2019.111002Search in Google Scholar

[28] Ziadat FM, Bruggeman A, Oweis TY, Haddad NI, Mazahreh S, Sartawi W, et al. A participatory GIS approach for assessing land suitability for rainwater harvesting in an arid rangeland environment. Arid LRes Manag. 2012;26:297–311.10.1080/15324982.2012.709214Search in Google Scholar

[29] Raj S. Rain Water Harvesting Potential of Pallavapuram Area of Meerut: A GIS Study. 12th Esri India User Conference; 2011.Search in Google Scholar

[30] Preeti P, Rahman A. Application of GIS in rainwater harvesting research: a scoping review. Asian J Water Environ Pollut. 2021;18(4):29–35.10.3233/AJW210040Search in Google Scholar

[31] Karani R, Joshi A, Joshi M, Velury S, Shah S. Optimization of rainwater harvesting sites using GIS. International Conference on Geographical Information Systems Theory, Applications and Management; 2019.10.5220/0007722302280233Search in Google Scholar

[32] Hari D, Ramamohan Reddy K, Vikas K, Srinivas N, Vikas G. Assessment of rainwater harvesting potential using GIS. IOP Conference Series: Materials Science and Engineering; 2018. p. 330.10.1088/1757-899X/330/1/012119Search in Google Scholar

[33] Gaikwad SD. Application of remote sensing and GIS in rainwater harvesting: A case from Goa. India: IJSER; 2015.Search in Google Scholar

[34] Choudhary S, Chouhan SS, Jain M, Panchal K, Bhardwaj Y. Development of rain water harvesting system through national highway profiles by using gis and field survey. Sustain Technol eJournal. 2019. 10.2139/ssrn.3348303.Search in Google Scholar

[35] Chiu Y-R, Tsai Y-L, Chiang Y-C. Designing rainwater harvesting systems cost-effectively in a urban water-energy saving scheme by using a GIS-simulation based design system. Water. 2015;7:6285–300.10.3390/w7116285Search in Google Scholar

[36] Ahmad M-uD. Site Suitability analysis using remote sensing & GIS for rain water harvesting. India: IJSER; 2016.Search in Google Scholar

[37] Nile BK. Effectiveness of hydraulic and hydrologic parameters in assessing storm system flooding. Adv Civ Eng. 2018;2018:1–17.10.1155/2018/4639172Search in Google Scholar

[38] He C-H, Liu C, He J-H, Shirazi AH, Mohammad-Sedighi H. Passive atmospheric water harvesting utilizing an ancient Chinese ink slab. Facta Universitatis, Series: Mech Eng. 2021;19(2):229–39.10.22190/FUME201203001HSearch in Google Scholar

[39] Rentachintala LRNP, Reddy MGM, Mohapatra PK. Urban stormwater management for sustainable and resilient measures and practices: a review. Water Sci Technol: A J Int Assoc Water Pollut Res. 2022;85(4):1120–40.10.2166/wst.2022.017Search in Google Scholar PubMed

Received: 2024-02-08

Revised: 2024-03-08

Accepted: 2024-03-13

Published Online: 2024-06-26

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

https://doi.org/10.1515/eng-2024-0009

Keywords for this article

data visualization; rainwater management; remote sensing; sustainable harvesting, sustainable watershed

Creative Commons

BY 4.0