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Article

A Proactive and Generalizable Framework for Urban Water Resilience in Semi-Arid Basins: Integrating Predictive Hydrology with LEED Certification

by
Mustafa Tunç
* and
Burcu Şeşeoğulları Bars
Department of Civil Engineering, Faculty of Engineering, Fırat University, Merkez, Elazığ 23100, Turkey
*
Author to whom correspondence should be addressed.
Sustainability 2026, 18(14), 7125; https://doi.org/10.3390/su18147125
Submission received: 7 September 2025 / Revised: 7 October 2025 / Accepted: 9 October 2025 / Published: 13 July 2026
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Abstract

This study addresses the dual challenges of seasonal water scarcity and urban flooding in the Garzan River basin, a region with a semi-arid climate. We propose and analyze an integrated water management system designed to mitigate these risks and promote both ecological and economic sustainability. Our methodology began with a comprehensive analysis of meteorological data from 2000 to 2024, which quantified the significant seasonal irregularity in the annual rainfall regime. The findings revealed that the bulk of the average 800 mm of rainfall occurs between January and May, while the summer months experience near-drought conditions. Based on this, we calculated the potential of various water conservation strategies. The system combines rainwater harvesting from a 1000 m2 roof and a 500 m2 parking lot, projected to collect 1020 m3 annually, with greywater reclamation and low-flow fixtures, which add a combined 400 m3 of annual savings. The total annual water savings of 1420 m3 were found to provide a gross annual economic benefit of $3550. Considering the installation and maintenance costs, the project’s payback period is estimated to be around 32 years. We also developed an annual precipitation prediction model providing a locally applicable early warning mechanism that forecasts total rainfall based on spring data. The use of proactive hydrometeorological data can improve the feasibility of long-term infrastructure projects to a certain extent. Finally, the proposed system’s design was confirmed to be eligible for multiple LEED certification credits, demonstrating its alignment with international sustainability standards. In conclusion, this research provides a comprehensive and viable solution that addresses local water issues and offers a valuable model for other regions facing similar challenges.

1. Introduction

Water is a fundamental necessity for the continuity of human life and the entire ecosystem. Throughout history, the establishment of settlements in areas close to water sources clearly demonstrates the vital importance of water. Today, water stands out as an indispensable resource in countless areas, from industrial production to domestic use, and from nutrition to health and hygiene [1,2,3]. Over the past two decades, water has become a strategic focus of global capital, with multinational water companies competing for control over freshwater resources with the support of global financial institutions [4,5,6]. The United Nations (UN) Water Development Report states that more than 3 billion people worldwide lack access to reliable water and predicts that water scarcity could reach 40% by 2030, pointing to serious challenges in meeting sustainable development goals [7,8,9]. The global water crisis is exacerbated by climate change, which disrupts hydrological cycles and intensifies extreme weather events like droughts and floods [10,11,12].
The water crisis is a complex issue resulting from a combination of both natural and human-induced factors, such as climate change, population growth, infrastructure deficiencies, and uninformed water consumption [13,14,15]. Despite its large land area, Turkey is not country rich in freshwater resources. Increasing drought and water stress are creating serious pressures on ecosystem balance and economic sustainability, making the efficient use and effective management of water resources imperative [16]. The situation is particularly critical in arid and semi-arid regions, which cover a significant portion of the globe and are highly vulnerable to water stress and climate change impacts [6,17,18,19]. In these areas, sustainable water management is not just an option but a necessity for survival, requiring integrated and innovative solutions [20,21,22].
Engineering solutions that promote water efficiency in urban and industrial areas are of great importance. Green building certification systems (such as LEED and BREEAM) prioritize water conservation as a key criterion [23,24,25]. Technologies that increase water conservation in buildings, such as low-flow faucets and dual-flush toilet systems, reduce water consumption [26,27]. Additionally, rainwater harvesting systems contribute to reducing water consumption and protecting groundwater resources by collecting and storing rainwater for use in landscape irrigation or cleaning [28,29,30,31,32,33,34]. Greywater recycling systems treat lightly contaminated water from bathrooms, sinks, and washing machines, making it suitable for reuse in irrigation or toilet tanks, thereby significantly reducing total water consumption [35,36,37,38]. The implementation of these technologies in a synergistic manner forms the core of integrated water management systems, which are now widely recognized as the most effective approach to urban water sustainability [39,40,41].
LEED (Leadership in Energy and Environmental Design) certification encourages the environmentally friendly and sustainable implementation of water management systems in buildings. These criteria promote the rational use of water and aim to prevent water wastage through the integration of innovative systems. The LEED framework provides a structured pathway for buildings to achieve water efficiency, offering a global benchmark for sustainable design and construction. The widespread adoption of such green building standards is critical for reducing the water footprint of urban areas and mitigating pressure on municipal water supplies [42,43].
The Garzan River basin, located in Turkey’s Southeastern Anatolia Region, faces significant challenges in terms of both water supply and flood management due to its semi-arid climate [44]. According to records from the General Directorate of Meteorology and the State Water Works, the majority of the basin’s annual average rainfall of 800 mm is concentrated between January and May, while rainfall drops to very low levels of 0–10 mm between June and August. This seasonal irregularity increases the risk of water scarcity during the summer months, while sudden and heavy downpours in the spring months pose a risk of flooding and water quality degradation by exceeding the capacity of the existing sewerage infrastructure [45,46,47,48,49,50].
The main innovation of this study is that it offers a highly applicable (high-utility) early warning tool tailored to the unique hydro-meteorological regime of the Garzan Basin, rather than the possessing complexity of traditional prediction models. The fact that our model is based solely on three months’ (March, April, May) cumulative rainfall data is not a scientific limitation but a conscious design decision. In the Garzan Basin, where approximately 60% of the annual total rainfall occurs during this period, using this critical three-month data provides water managers with a strategic window to adjust their annual water allocation plans and the operational intensity of gray water systems 6–8 months before the risk of water scarcity begins in the summer months (at the end of May). Unlike traditional complex models, the developed linear correlation model is easily understandable and usable by local authorities with limited resources. This ‘ease of use’ and ‘local validity’ constitute the methodological innovation of the study.
This study presents an integrated water management framework that is adaptable to semi-arid regions undergoing rapid urbanization on a global scale, rather than a local solution applied in the Garzan Basin. The main objective of this study is to develop an integrated water management design that will respond to this dual risk profile in the Garzan basin and support seasonal advance planning of annual water management. In the study, long-term meteorological data for the period 2000–2024 were analyzed in detail, and the seasonal fluctuations in the basin’s annual and monthly rainfall regime were quantitatively identified. The authors would like to note that our analyses include data up to 2024, but the figures specifically show the period 2000–2011 to validate the model’s performance and highlight the most pronounced fluctuations. Subsequently, the potential for rainwater harvesting, greywater recycling, and water efficiency measures was calculated at a specific project site scale, and the economic feasibility of these systems and their contributions to LEED certification were evaluated. This holistic approach aims to provide significant contributions to sustainable water management practices in the Garzan River basin by bringing together technical solutions that will reduce regional drought and flood risks. The novelty of the current study is its integrated solution to the dual problems of water scarcity and flood risk in a semiarid region. A holistic system combining rainwater harvesting, graywater recycling, and water-efficient fixtures is proposed. The main novel contribution is the development of a providing a locally applicable early warning mechanism that predicts annual rainfall based on spring precipitation. This model enables proactive water management planning.

2. Materials and Methods

This study adopted comprehensive meteorological data analysis, water-saving-potential calculations, and economic feasibility analysis methods to evaluate integrated sustainable water management strategies in the Garzan River Basin. The concentration of settlements along the Garzan River and other watercourses proves that the river has historically been a critical resource for life, agriculture, and settlement dynamics in the region. (Figure 1).

2.1. Field of Work

The Garzan River Basin, located in the Southeastern Anatolia Region of Turkey, is the study area of this research. The region exhibits semi-arid climate characteristics and experiences significant seasonal irregularities in its annual rainfall regime. This situation brings with it water shortages, especially in the summer months, and flood risks in the spring months. The details of the specific project site (surface areas) examined as a case study in the thesis have formed the basis for calculations of rainwater harvesting potential [52,53].

2.2. Meteorological Data Analysis

The meteorological data used in the study were obtained from the records of the Batman Meteorological Station (sources: General Directorate of Meteorology and State Water Works) covering the period between 2000 and 2024. These data include annual total precipitation amounts, monthly extreme precipitation values (precipitation amounts for the driest and wettest months), and long-term averages (1982–2011) of monthly precipitation and temperature values. The obtained data were analyzed using Excel and IBM SPSS Statistics 22 software to determine water imbalances and seasonal characteristics in the basin.

2.3. Water Conservation Potential Calculations

Rainwater Harvesting (RWH): Rainwater harvesting potential was calculated based on a specified 1000 m2 roof area and 500 m2 parking area (total 1500 m2 collector surface area). The annual volume of harvestable rainwater, VRWH (m3/year), was calculated using the following equation [54,55].
VRWH = A × R × Cf × Ef
Here, A represents the total collection surface area (m2); R is the average annual rainfall for the basin (m/year), based on the long-term meteorological data; Cf is the runoff coefficient, which accounts for surface properties and is a dimensionless factor (e.g., typically 0.85–0.90 for roofs and 0.70–0.80 for parking lots); and Ef is the system efficiency factor (85%), which accounts for losses such as first-flush diversion, evaporation, and leakages. This methodology provides a robust and replicable framework for calculating rainwater potential in other urban environments with similar rainfall patterns.
Greywater Recycling (GW, Rec): The potential volume of reusable greywater, VGW (m3/year), was estimated based on typical daily per capita production and system efficiency. A daily per capita greywater production rate of 100 L was assumed, a value consistent with standards from the World Health Organization [56,57]. The calculation for annual usable greywater is given by:
VGW = Ninhabitants × Qdaily × 365 × (1 − Lloss)
Here, Ninhabitants is the number of inhabitants in the building (assumed for the case study), Qdaily is the daily per capita greywater production (0.1 m3/day), and Lloss is the system loss factor (15%), including operational inefficiencies and evaporation. This method is readily adaptable to other residential or commercial buildings by adjusting the population size.
Low-Flow Fixtures: The potential for additional water savings through the use of low-flow faucets, showerheads, and sensor-activated systems was estimated based on similar projects in the literature and standard savings rates [58,59].

2.4. Economic Feasibility Analysis

A cost–benefit analysis was conducted to assess the economic sustainability of integrated water management systems (YSH and GSGD). The analysis utilized parameters such as installation costs ($50,000), annual operating and maintenance costs ($2000/year), and water cost per cubic meter ($2.5/m3). Financial metrics such as payback period and net present value (NPV) were calculated to assess the financial attractiveness of the project [60,61,62]. A comprehensive cost–benefit analysis was conducted to assess the financial viability of the integrated system. The analysis was based on three key parameters: total initial installation cost (Icost), annual maintenance cost (Cmaint), and the economic value of water savings (Bwater). The annual net savings (Snet) was calculated using Equation (3):
Snet = (VRWH + VGW + VLF) × Cunit − Cmaint
where VLF represents the volume from low-flow fixtures and Cunit is the unit cost of water (2.5/m3). The payback period was determined by dividing the initial installation cost by the annual net savings.
The assumption of 100 L/person/day for gray water production is based on detailed water usage studies conducted in residential buildings in Turkey. This value is a conservative and locally calibrated figure representing an average of 55–65% of total water consumption from baths/showers, sinks, and washing machines. This value is lower than the international standard of 120–150 L/person/day of gray water production in the US or EU [27]. The recovery efficiency of gray water treatment systems (85%) is a standard performance achieved by conventional membrane bioreactors (MBR) or hybrid filtration systems under optimal operating conditions. This factor assumes that the system requires a high level of maintenance and continuous water quality monitoring. This value has been used to demonstrate the system’s maximum water recovery potential [1]. Actual operational efficiency may be lower, especially under poor maintenance conditions; therefore, this risk should be assessed in our Sensitivity Analysis. As the results of the prediction model quantitatively determined the annual water deficit risk in the Garzan Basin, the design of integrated water management solutions to close this gap constituted the next phase. After determining the technical capacity of the integrated system, the project’s long-term feasibility and sustainability commitment were evaluated using economic feasibility and international standards (LEED) metrics.
The economic analysis is based on static cost–benefit analysis principles to evaluate the initial feasibility of water management projects at the regional level. The assumptions of a fixed water price ($2.5/m3) and fixed Operation and Maintenance (O&M) costs reflect market conditions at the time of the initial investment decision. This approach establishes a baseline scenario to calculate the system’s potential Annual Net Benefit ($1550) and Payback Period (32 years). However, we recognize that this model does not incorporate dynamic macroeconomic factors such as inflation, technological change, and future policy changes. To address these limitations and test the robustness of the baseline result, a Sensitivity Analysis has been included in the analysis. A single-factor sensitivity analysis has been performed to test the robustness of the economic results. To simulate the long-term impact of factors such as inflation and policy risks, the two most decisive variables, water price and installation cost, were varied within ranges of ± 15% and ± 20%.
Sensitivity analysis indicates that a 20% increase in water prices (whether politically driven or due to scarcity) could reduce the payback period to approximately 26 years. Conversely, a 20% decrease in water prices would extend the payback period to 40 years, significantly reducing the project’s financial attractiveness. These findings scientifically demonstrate that the long-term feasibility of the system is critically dependent on the water tariff policy in the Garzan Basin and the severity of the current water scarcity. In conclusion, while a 32-year payback period is our base-case scenario, the sensitivity analysis confirms that the environmental benefit outweighs the fixed financial return because the project acts as insurance against water scarcity risk.

2.5. LEED Certification Assessment

The proposed integrated water management strategies have been assessed to determine which “Water Efficiency (WE)” and “Innovation in Design (ID)” credits they could contribute to under the LEED (Leadership in Energy and Environmental Design) certification system [63]. Based on LEED v4 or v4.1, the potential point equivalents for rainwater management, water usage reduction, and advanced technology applications have been evaluated [64,65]. In the current study, LEED credit assessment is based on LEED v4 or v4.1. Potential differences exist between versions. In the current study, data from 2000–2011 were used for model training, while data from 2012–2024 were used for independent model validation.

3. Results and Discussion

In this section, scientifically valuable graphs that were created based on the data obtained are presented, and detailed comments and conclusions are made for each graph. In the graph presented in Figure 2, the X-axis represents the years (2000–2011), while the Y-axis represents the annual total rainfall amount (mm). Each year is marked with a point, clearly illustrating the changes over time.

3.1. Results

Figure 2 shows that the total annual rainfall in the Garzan River Basin varied significantly between 2000 and 2011. In particular, while a high value of 1739.2 mm was recorded in 2004, the drop to 592.2 mm in 2008 highlights the severity of fluctuations in the annual rainfall regime. Such high annual variations (approximately a 200% difference) indicate that the basin’s water resources management is highly fragile and vulnerable to the irregular rainfall patterns brought about by climate change. This finding emphasizes the need to focus not only on average values but also on extreme years in long-term water resource planning, and the necessity of designing water conservation and storage capacities that can manage these fluctuations. These sharp declines and increases between years are considered to pose serious risks, particularly for agricultural activities and urban water supply.
The graph presented in Figure 3 shows the years (2000–2011) on the X-axis and the amount of precipitation (mm) on the Y-axis. Two different colored bars for each year represent the values for the driest and wettest months. Figure 2 dramatically highlights the extreme variations in seasonal rainfall distribution in the Garzan Basin between 2000 and 2011. As seen in the graph, there is a huge difference between the rainfall amounts in the driest months (mostly in the 0–10 mm range) and the rainfall amounts in the wettest months (exceeding 400 mm in some years). For example, in 2004, only 0.0 mm of rainfall was recorded in the driest month, while 417.8 mm of rainfall fell in the wettest month. This sharp contrast indicates that the region’s hydrological regime exhibits a high degree of seasonality and that a significant portion of water resources is concentrated in a short period of the year. This situation underscores the need for water storage systems (e.g., rainwater harvesting storage tanks) to be designed with sufficient capacity to meet water demand, particularly during dry periods. Additionally, the critical importance of effective drainage and storage solutions during periods of heavy rainfall for flood risk management is supported by this graph.
Figure 4 details the monthly rainfall regime of the Garzan Basin for the period 2012–2024 based on long-term averages. As clearly shown in the graph, the majority of rainfall is concentrated in the winter and spring months (January–May). January, February, March, and April have the highest average rainfall values, while June, July, and August stand out as dry months with almost no rainfall or very low values. This average distribution supports the extreme rainfall differences shown in Figure 3 and confirms the basin’s characteristic seasonal water imbalance. This graph scientifically validates that water resource management strategies should focus on collecting and storing water during periods of abundant rainfall, thereby meeting water demand during the dry summer months. The potential of rainwater harvesting systems to capture winter and spring rainfall is further emphasized by this monthly distribution. The monthly average precipitation distribution in Figure 4 is based on long-term data for the period 2012–2024.
The graph presented in Figure 5 shows the percentage distribution of the total 1420 m3/year savings (rainwater: ~72.0%, gray water: ~21.0%, low-flow fixtures: ~7.0%). Figure 4 illustrates the contribution of the proposed integrated water management strategies for the Garzan River Basin to the total annual water savings. The graph clearly shows that a large portion (~72.0%) of the total savings of 1420 m3/year comes from rainwater harvesting (1020 m3/year). Greywater recycling (~21.0% with 300 m3/year) and low-flow fixture applications (~7.0% with 100 m3/year) also provide significant complementary contributions. This finding highlights that rainwater potential constitutes the largest savings category, depending on the region’s climatic characteristics. Therefore, it supports the conclusion that priority should be given to large-scale rainwater harvesting and storage systems in sustainable water management projects [66,67,68]. Additionally, the potential of gray water and efficient fixtures to increase total water independence in an integrated system is emphasized, as these systems complete the indoor water consumption cycle.
The infographic presented in Figure 6 analyzes the financial dimension of the integrated water management system (rainwater harvesting and gray water recycling) in the Garzan Basin. Considering that the initial installation cost is $50,000, the annual gross water cost savings are $3550 (1420 m3/year × $2.5/m3) and an annual operating/maintenance cost of $2000, resulting in an annual net savings of $1550 ($3550–$2000). Figure 6 illustrates the payback period (approximately 32 years) by comparing the size of the initial investment and the annual net benefit. The long payback period demonstrates that such environmental infrastructure projects typically require high initial investments but create economic value in the long term by reducing operational costs and providing environmental benefits. Additionally, it is clear that these projects should be evaluated not only for their financial return but also for their multi-dimensional contributions, such as water security, ecosystem health, and social benefits, in order to achieve environmental sustainability goals.
A long payback period (32 years) is standard for integrated water management and environmental sustainability projects, unlike typical commercial projects. This long-term payback emphasizes that the financial value of the system must be balanced with the environmental and social capital it will provide. The current study provides long-term resilience for society against drought and flood risks associated with climate change, creating a significant indirect benefit by preventing the potential economic costs of future water restrictions and floods. The 32-year investment should be seen as a strategic public investment in water security, supporting sustainable urbanization in the Garzan Basin. Short-term commercial returns (Net Benefit) are of secondary importance in such projects, where long-term ecological and social sustainability is the primary goal.
Figure 7 highlights the significant contributions of the proposed integrated water management systems in the Garzan River Basin to the LEED (Leadership in Energy and Environmental Design) certification process. This system, which earns a total of 7 LEED points, makes its largest contribution with 3 points from the ‘Water Use Reduction’ (WE) category, reflecting the importance of direct water savings achieved through low-flow fixtures, graywater recycling, and rainwater utilization. The 2 points earned in the ‘Rainwater Management’ category confirm the potential to reduce flood risk in the basin and utilize rainwater as a resource. Additionally, the 1 point each earned from the ‘Innovation in Design’ and ‘Measurement & Verification’ credits demonstrates that the project not only achieves water savings but also adopts an innovative approach and provides performance monitoring capabilities. This graph clearly demonstrates the critical role that integrated water management applications play in achieving environmental sustainability goals and developing projects that comply with green building standards.
Figure 8 shows the performance of the annual average precipitation prediction model developed for the Garzan River Basin. This model was derived using precipitation heights for March (Rmarch), April (Rapril), and May (Rmay). The mathematical expression of the model is presented in Equation (4). This equation reflects the decisive role of spring rainfall on the annual total rainfall in the Garzan River Basin. The correlation coefficient (R2) value evaluating the model’s performance has been determined as 0.95. The R2 value of 0.95 in the graph indicates that the developed model can explain 95% of the annual average rainfall variance. This proves that there is an extremely strong and positive linear relationship between the measured annual average rainfall values and the predicted values. An R2 value close to 1 indicates that the rainfall in March, April, and May is a highly reliable indicator for predicting the annual rainfall amount in the Garzan River Basin. This supports the critical importance of these three months in terms of the basin’s hydrological cycle and water resource renewal. In the scope of the present study, Equation (4) was developed as a correlation-based early warning model for basins where more than 50% of the annual precipitation occurs in a single season.
Rmean = 1.93 × Rmarch + 1.04 × Rapril + 1.43 × Rmay
The proximity of the data points in the graph presented in Figure 8 to the regression line (dashed line) indicates that the model’s predictions are quite close to the measured values. The fact that the points generally follow the 1:1 line (y = x) indicates that the model does not show a tendency to overestimate or underestimate, i.e., its bias is low. This shows that the model performs consistently even in years with different rainfall regimes.
When examining the model’s coefficients (Rmarch: 1.93, Rapril: 1.04, Rmay: 1.43), it is seen that the rainfall in March and May has a greater effect on the annual total rainfall than the rainfall in April. In particular, the fact that the coefficient for March is larger than the others suggests that snowmelt at the end of winter and spring rainfall make significant contributions to the basin’s annual water budget. These months may also be periods when soil moisture increases and surface runoff intensifies.
The success of this model highlights how critical seasonal forecasts are for water resource management in the Garzan River Basin. The rainfall pattern in March, April, and May can provide an early indicator of the overall water potential for that year, enabling preventive measures to be taken, particularly in areas such as agricultural irrigation, drinking water supply, and energy production. The model’s high predictive power increases the predictability of annual rainfall amounts. This provides a significant advantage for the sizing and planning of rainwater harvesting systems. More reliable estimates of potential annual water harvest volumes will help optimize storage capacities and enable their effective use as a complementary source during periods of water scarcity. Heavy rainfall in March, April, and May plays a key role in determining the harvestable water volume.
Rainfall data obtained from the model plays a complementary role in assessing the applicability and effectiveness of greywater recycling systems. In high-rainfall years, rainwater harvesting takes priority, while in low-rainfall years when the risk of drought increases, alternative water sources such as gray water recycling become even more important. This model can help inform decisions about which water management strategy will be more effective at what time by providing information about the basin’s overall water budget. LEED criteria encourage water efficiency and the use of renewable water sources. This model can contribute to achieving the water efficiency targets required in LEED certification processes by determining the rainwater harvesting potential for new or existing structures in the Garzan River Basin. The reliable predictions provided by the model form a scientific basis for the sustainable use of regional water resources.
The developed prediction model was developed using data from 2000–2011 to establish correlations based on at least 10 years of reliable historical data. This period represents a sufficient time frame to optimize the model’s basic parameters. Data from 2012–2024 was used to evaluate the generalized prediction capability of the developed model on an independent, unseen data set. To address the risk of overfitting and prove the robustness of our model, the Cross-Validation technique was applied in our analyses. Specifically, the 2012–2024 period data, independent of the 2000–2011 data set used in training the model, was used to independently validate the model’s prediction performance. This scientifically confirms that the model is generalizable not only to the training data but also to the more recent meteorological conditions of the Garzan Basin. The model performance obtained in this independent validation set (e.g., Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) values) yielded results similar to those in the training period. These findings invalidate claims of data selection bias and overfitting, as the model’s predictive ability demonstrated high consistency even on unseen data.
Figure 9 shows how accurate the annual average precipitation prediction model developed for the Garzan River Basin is for different years, expressed as a percentage of Absolute Relative Deviation (ARD). ARD is a measure that indicates the percentage deviation of the predicted value from the actual value. Positive ARD values indicate that the model overestimates the actual value, while negative ARD values indicate that it underestimates the actual value. The thick black line on the graph (ARD = 0) represents the ideal situation where the model makes error-free predictions. The ARD (%) value was calculated using Equation (5) [69,70,71].
A R D = R m e a s u r e d − R p r e d i c t e d R m e a s u r e d × 100
Since the values in the graph presented in Figure 9 show deviations in both positive and negative directions, it is likely that the absolute value of ARD was not taken, but only the relative deviation percentage (RD) was used. This interpretation is consistent with the presence of both positive and negative values in the graph. The fact that the majority of the points in the graph fall within or near the ±10% range indicates that the developed model generally predicts the annual rainfall amount in the Garzan River Basin with an acceptable margin of error. In particular, the model’s predictions are seen to be quite close to the actual values at the beginning and end of the 2000 s. In the years 2000, 2005, 2006, 2007, 2008, and 2009, the ARD/RD values are within the ±5% range or very close to it. (e.g., approximately + 2% in 2000, approximately −2% in 2005, approximately −4% in 2007, and approximately 0% in 2008 and 2009). This indicates that the model predicted the annual total precipitation amount for these years with a high degree of accuracy. It can be assumed that the rainfall patterns in March, April, and May during these years exhibit a “normal” or “typical” distribution, enabling the model to demonstrate its expected performance in predicting annual total rainfall.
The year 2003 was the year in which the model showed the greatest deviation. An ARD/RD value of approximately −18% indicates that the model underestimated the actual annual total precipitation for that year by 18% (low estimate). There may be several possible reasons for this. In 2003, unexpectedly high and intense precipitation may have occurred in months other than the spring months (March, April, May) that form the basis of the model (e.g., during the summer or fall seasons). Such unusual off-season precipitation can cause significant deviation because it falls outside the model’s prediction range. In some years, the seasonal distribution of rainfall can deviate significantly from the average. The year 2003 may have deviated from the typical spring-annual total relationship assumed by the model. In 2004, the model appears to have overestimated the annual total rainfall by approximately 8%. A possible reason for this is that in 2004, the share of rainfall in March, April, and May within the annual total was more dominant than the model anticipated, or that above-average rainfall in these months caused the model to estimate the annual total to be higher than it actually was.
ARD/RD analysis supports the model’s overall high reliability. Low deviation values for most years indicate that this model can be used as an important tool for estimating annual water potential in the Garzan River Basin. This reliability provides a solid basis for operational decisions such as water resource allocation planning, drought risk assessment, and irrigation scheduling. Significant deviations, such as those observed in 2003, emphasize the need to consider uncertainty and risk factors in integrated water management strategies. When planning applications such as rainwater harvesting and gray water recycling, the effects of unexpected events such as off-season rainfall or extreme weather events should also be considered alongside the model’s predictions. In years with extremely low predictions (e.g., 2003), the role of complementary water sources (gray water, deep well water) becomes even more important. A detailed analysis of years with high deviations can guide future improvements to the model. For example, integrating specific off-season rainfall or extreme meteorological events into the model could further improve prediction accuracy. Using a broader dataset or testing different machine learning algorithms could help reduce the model’s deviations.
The Absolute Relative Deviation (ARD) graph in Figure 9 confirms that the developed regression model generally exhibits high accuracy in annual precipitation estimates for the Garzan River Basin. Low deviations for most years demonstrate that the model is a reliable tool for water resource management and sustainable practices. However, the significant deviations observed in certain years, such as 2003 and 2004, highlight the model’s limitations and the importance of considering the effects of off-season rainfall or abnormal climatic events. This analysis underscores the necessity of flexibility and preparedness for different scenarios in integrated water management approaches.
Despite the model’s high R2 value, ARD analysis shows that the prediction error exceeded reasonable limits in some years. The low prediction deviation of 18% observed in 2003 is particularly noteworthy. This deviation is due to unusual and intense rainfall events occurring in seasons other than the March–May spring rainfall, which forms the basis of the model, especially in late summer or autumn months. Our model is overly dependent on spring rainfall, which dominates the annual rainfall regime. These large deviations are an important scientific finding indicating increased climate variability in the Garzan Basin and a shift in rainfall away from its traditional seasonal distribution. This limitation presents a critical area for improvement in future studies. The model’s development should aim to better capture not only spring rainfall but also extreme off-season rainfall events. This in-depth analysis reveals not simply the model’s failure but its value as a diagnostic tool for increasing climate variability in semi-arid regions. While our model’s current form serves as an early warning system for water managers, the deviation analysis provides evidence of change in regional climate models.

3.2. Discussion

This study conducted in the Garzan River Basin addresses two critical issues in water resource management in the region (summer drought and spring flood risks) and offers integrated solutions. The analyzed meteorological data (Figure 1, Figure 2 and Figure 3) scientifically prove that the region exhibits high climatic variability and that the seasonal distribution of water resources is unbalanced. Large fluctuations in annual total rainfall and minimum rainfall values during dry months confirm the high potential for water stress in the basin. This situation necessitates not only the conservation of existing water resources but also the use of alternative water sources (such as rainwater and gray water).
The most significant novel contribution of this study is the development of a highly accurate annual precipitation prediction model. This model (R2 = 0.95), derived from spring rainfall data (March–May), provides a proactive tool for water management, which is a critical advancement for a semi-arid region like the Garzan basin. Unlike most studies that rely on historical data for reactive planning (e.g., [29]), our model offers a predictive capability that enables forward-looking strategies. The high coefficient of determination (R2) demonstrates an exceptional fit, surpassing the predictive accuracy of similar models in the literature for other semi-arid regions. This high predictive power allows for more reliable sizing and planning of rainwater harvesting systems and provides a scientific basis for operational decisions like drought risk assessment and water resource allocation.
The integration of systems such as rainwater harvesting and greywater recycling, as shown in Figure 5, provides significant savings in total water consumption. This finding is consistent with global trends demonstrating the effectiveness of such decentralized systems [32,34]. While many studies focus on the efficiency of individual systems, our holistic approach highlights the synergistic benefits of combining them to create a resilient water loop. This strategy not only reduces the pressure on drinking water sources but also helps minimize flood risks by alleviating the burden on drainage systems in cities, a key finding that aligns with the principles of Sustainable Urban Drainage Systems (SUDS) [30]. To achieve certification, the proposed greywater system must meet specific water quality standards, and it is important to note that this will require further on-site testing and design in a real-world application. Furthermore, the types of data to be collected (e.g., precipitation, water use, and system performance) should be thoroughly specified to support the model’s predictions and inform future improvements.
The economic feasibility analysis (Figure 6) shows that integrated systems have a long payback period. This finding is comparable to other long-term green infrastructure investments [60,61] and underscores the need to evaluate such projects based on their long-term ecological and social benefits rather than short-term commercial concerns. Given the increasing costs of water scarcity and the risks posed by climate change, such investments are of strategic importance for ensuring future water security. These findings reinforce the growing academic consensus that public funding and policy support are crucial for widespread adoption of sustainable urban water systems. The assessment based on LEED certification criteria (Figure 7) further validates this approach, showing that the proposed systems align with internationally recognized standards, thereby increasing the project’s potential for international investment and serving as a model for achieving sustainable development goals. Given the climate of the region under study, freeze protection measures for water storage tanks are essential, and designs such as underground tanks or insulated aboveground tanks are essential to prevent freezing and potential damage.
The potential 7 points earned from LEED certification demonstrate the proposed integrated water system’s compliance with international sustainability standards. Earning these points depends not only on calculations but also on ensuring the system’s operational performance. These credits will be met not only by the theoretical savings potential of low-flow fixtures, but also by real-world measurement and verification. Our system’s entry into the LEED certification process requires continuous scientific monitoring of the project not only during the design phase but also during the operational process. LEED certification is a process mandated by third-party verifiers accredited by the U.S. Green Building Council (USGBC). These verifiers independently validate all performance targets of the system (water savings, energy efficiency, and water quality). This mandatory verification mechanism demonstrates that the theoretical savings calculations in our paper are guaranteed at the actual performance level. The proposed integrated water system is designed in the context of a new residential or commercial development planned in the Garzan Basin. This context is based on a practical project with assumptions of 1000 m2 of roof area and 500 m2 of parking area. Monitoring this project in a pilot phase and continuously collecting data will form the basis for future scientific validation studies in our study.
Among the limitations of this study are the fact that the cost and benefit parameters in the economic analysis are based on general assumptions and that the project site is on a pilot scale. However, the replicability of our methodology is a key strength. The proposed models and calculation methods can be applied to other semi-arid regions with similar climate patterns by adapting the specific local data (rainfall, water prices, etc.). Future studies may include detailed case studies for larger-scale applications, modeling of system performance under different climate scenarios, and a more comprehensive assessment of socio-economic benefits (e.g., savings in health costs, ecosystem services).

4. Conclusions and Recommendations

This study highlights the importance of integrated and sustainable solutions to address water management challenges caused by climate irregularities in the Garzan River Basin. Significant variability in annual and seasonal rainfall patterns requires the simultaneous management of water scarcity and flood risks in the region. It has been demonstrated that the implementation of rainwater harvesting and graywater recycling systems can result in significant savings in annual water consumption and that these systems can meet international sustainability standards through LEED certification. The authors state that their proposal for a real-time monitoring system is a future step for a full-scale project. Such a system is crucial for data validation and performance optimization. Based on the findings, the following recommendations are presented:
➢
Pilot projects and incentive mechanisms should be developed to promote rainwater harvesting and grey water recycling systems in urban and rural areas in the Garzan River Basin and other regions with similar climatic characteristics.
➢
Local expertise and technical capacity should be developed in the design, installation, and maintenance of such systems.
➢
Legal regulations and policies that encourage and facilitate sustainable water management practices (e.g., tax breaks, subsidies, mandatory green building standards) should be developed.
➢
Education and awareness campaigns should be organized to raise public awareness about the importance of water conservation and the use of alternative water sources.
➢
The potential impacts of future climate change scenarios on the water resources of the Garzan River Basin should be modeled in greater detail, and water management plans should be updated according to these projections. This is critical for ensuring long-term water security.
➢
Continuously monitoring the performance of implemented systems and collecting data will form the basis for future optimizations and more accurate modeling.
➢
The regression model developed in this study can accurately predict the annual average rainfall in the Garzan River Basin based on rainfall levels in March, April, and May. This model is a critical tool for the sustainable management of water resources in the basin, providing important information for the planning and implementation of rainwater harvesting and integrated water management strategies. The model’s predictions provide a scientific basis for efforts to mitigate the potential impacts of climate change and use water resources more efficiently. The developed statistical model, a core novelty of this study, provides a crucial tool for predictive and proactive water management in the basin.
➢
The developed methodology provides a framework that can be directly applied to semi-arid urban areas beyond the Garzan Basin that exhibit similar high seasonal variability. Using LEED criteria as a methodological tool can increase the transparency and public trust in projects by aligning local water management decisions with international standards through third-party verification requirements. This provides a critical market signal for the rapid adoption of water management solutions at the regional level.
➢
Future research should validate the system’s theoretical feasibility with real-world performance. This will require pilot-scale implementation of the proposed integrated system and dynamic calibration of the prediction model and water recovery efficiency (assuming 85%) using on-site validation data. Furthermore, expanding the model to include climate indices (e.g., ENSO/NAO) will further enhance its predictive power against extreme weather events.
These recommendations will make the region more resilient to future water challenges by improving water security and promoting environmental sustainability in the studied basin.

Author Contributions

Conceptualization, M.T. and B.Ş.B.; Methodology, M.T. and B.Ş.B.; Software, M.T.; Validation, M.T. and B.Ş.B.; Formal analysis, M.T.; Investigation, M.T. and B.Ş.B.; Resources, M.T. and B.Ş.B.; Data curation, M.T. and B.Ş.B.; Writing—original draft, M.T.; Writing—review & editing, M.T. and B.Ş.B.; Visualization, M.T.; Supervision, M.T.; Project administration, M.T.; Funding acquisition, M.T. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by Fırat University Scientific Research Projects Coordination Unit (FÜBAP) with grant number MF.25.142.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Location and geographical context of the Garzan River basin from the world [51].
Figure 1. Location and geographical context of the Garzan River basin from the world [51].
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Figure 2. Changes in annual total rainfall amounts in the Garzan Basin over the years.
Figure 2. Changes in annual total rainfall amounts in the Garzan Basin over the years.
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Figure 3. Annual precipitation data used for training the precipitation prediction model (2000–2011).
Figure 3. Annual precipitation data used for training the precipitation prediction model (2000–2011).
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Figure 4. Monthly precipitation distribution in the Garzan Basin based on long-term averages.
Figure 4. Monthly precipitation distribution in the Garzan Basin based on long-term averages.
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Figure 5. Components of total annual water savings achieved through integrated water management in the Garzan River Basin.
Figure 5. Components of total annual water savings achieved through integrated water management in the Garzan River Basin.
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Figure 6. Cost and annual savings distribution of integrated water management system installation.
Figure 6. Cost and annual savings distribution of integrated water management system installation.
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Figure 7. LEED certification credits and integrated water management contribution.
Figure 7. LEED certification credits and integrated water management contribution.
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Figure 8. Performance of the Garzan River Basin annual average precipitation prediction model.
Figure 8. Performance of the Garzan River Basin annual average precipitation prediction model.
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Figure 9. Annual Relative Deviation (ARD) percentages by year for the Garzan River Basin annual precipitation prediction model.
Figure 9. Annual Relative Deviation (ARD) percentages by year for the Garzan River Basin annual precipitation prediction model.
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Tunç, M.; Şeşeoğulları Bars, B. A Proactive and Generalizable Framework for Urban Water Resilience in Semi-Arid Basins: Integrating Predictive Hydrology with LEED Certification. Sustainability 2026, 18, 7125. https://doi.org/10.3390/su18147125

AMA Style

Tunç M, Şeşeoğulları Bars B. A Proactive and Generalizable Framework for Urban Water Resilience in Semi-Arid Basins: Integrating Predictive Hydrology with LEED Certification. Sustainability. 2026; 18(14):7125. https://doi.org/10.3390/su18147125

Chicago/Turabian Style

Tunç, Mustafa, and Burcu Şeşeoğulları Bars. 2026. "A Proactive and Generalizable Framework for Urban Water Resilience in Semi-Arid Basins: Integrating Predictive Hydrology with LEED Certification" Sustainability 18, no. 14: 7125. https://doi.org/10.3390/su18147125

APA Style

Tunç, M., & Şeşeoğulları Bars, B. (2026). A Proactive and Generalizable Framework for Urban Water Resilience in Semi-Arid Basins: Integrating Predictive Hydrology with LEED Certification. Sustainability, 18(14), 7125. https://doi.org/10.3390/su18147125

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