*Article* **Predicting Snowmelt Runoff at the Source of the Mountainous Euphrates River Basin in Turkey for Water Supply and Flood Control Issues Using HEC-HMS Modeling**

**Selim ¸Sengül \* and Muhammet Nuri ˙Ispirli**

Department of Civil Engineering, Faculty of Engineering, Atatürk University, Erzurum 25100, Turkey; m.nurii@hotmail.com

**\*** Correspondence: ssengul@atauni.edu.tr; Tel.: +90-442-2314569

**Abstract:** Predicting the runoff from snowpack accumulated in mountainous basins during the melting periods is very important in terms of assessing issues such as water supply and flood control. In this study, the Hydrological Engineering Center–Hydrological Modeling System (HEC-HMS) was used to simulate snowmelt runoff in the Kırkgöze–Çipak Basin that has a complex topography where altitude differences range from 1823 m to 3140 m above the sea level. The Kırkgöze–Çipak Basin, located in eastern Turkey, is a basin where snowfall is highly effective during the cold season. There are three automatic meteorology and snow observation stations and three stream gauge stations in the basin, which are operated especially for the calibration and validation of hydrological parameters at different altitudes and exposures. In this study, the parameters affecting snow accumulation– melting and runoff were investigated using the simulations on an hourly basis carried out over a three-year period for temporal and spatial distribution at the basin scale. Different from previous studies focusing on the rate of snowmelt, the temperature index method, which is calculated with physically-based parameters (R<sup>2</sup> = 0.77~0.99), was integrated into the runoff simulations (R<sup>2</sup> = 0.84) in the basin. The snowmelt-dominated basin is considered to be the source of the headwaters of the Euphrates River.

**Keywords:** snowmelt; hydrologic modeling; ATIMR; HEC-HMS; Euphrates River; Kırkgöze–Çipak Basin

#### **1. Introduction**

Water is the source of life and is probably the most valuable natural asset in the Middle East. Within this perspective, the history of water management is nothing less than the history of humankind. From the inception of our species, coping with the availability—or unavailability—of water resources has been an essential element of human beings' strategies for survival and wellbeing [1]. The two largest rivers in Western Asia, the Euphrates and Tigris, flow in Turkey, Syria, Iran, Iraq, and Saudi Arabia. The Euphrates and Tigris basins are fed predominantly by snow precipitation. Approximately two-thirds of this occurs in winter, and the snow may remain for half a year [2]. Consequently, where water supplies are under stress, such as the semiarid regions of the Mediterranean basins, the activity of snowmelt-derived streamflows are extremely important [3].

The mountain snowfall acts as a natural reservoir for storing precipitation during the cold season, and during the spring months it melts and flows to the rivers. Understanding when the snow melts and the resulting streamflow occurs is essential to be able to effectively manage water resources. Analyses of how the amount and timing of these hydrological quantities vary are crucial to the water supply systems in mountain regions [4]. It is particularly important in the Euphrates and Tigris basins where there are large reservoirs. Results obtained from the hydrological modeling system algorithms of the snowmeltdominated mountainous Kırkgöze–Çipak Basin improve the accuracy of water resource simulations and help in the planning and operation of the Euphrates River flows.

**Citation:** ¸Sengül, S.; ˙Ispirli, M.N. Predicting Snowmelt Runoff at the Source of the Mountainous Euphrates River Basin in Turkey for Water Supply and Flood Control Issues Using HEC-HMS Modeling. *Water* **2022**, *14*, 284. https://doi.org/ 10.3390/w14030284

Academic Editors: Dengfeng Liu, Hui Liu and Xianmeng Meng

Received: 15 December 2021 Accepted: 15 January 2022 Published: 18 January 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

To date, researchers have introduced a wide variety of modeling frameworks to model the hydrological process [5–7]. In general, these modeling frameworks can be divided into three main groups: conceptual, physically-based, and machine learning models. Conceptual and physically-based models can be used for research purposes to improve knowledge and understanding of the hydrological processes that govern the real-world system. On the other hand, machine learning models create a direct mapping between precipitation and runoff variables and infer their relationships based on historical observations with machine learning algorithms without prior knowledge of internal hydrological processes [8]. Hydrological models are also developed and used for simulation and forecasting tools that allow decision-makers to make the most effective decisions for planning and operations, taking into account the interactions of the physical, ecological, economic, and social aspects of the real-world system. In addition, real-time flood forecasting and warning, flood frequency forecasting, flood route and overflow forecasting, climate and land-use change, and impact assessments of integrated basin management are examples of other applications in which the hydrological models are used [7,9].

In regions where most of the precipitation falls as snow during the winter months as the altitude increases, the snowmelt component of the hydrological models is vital for water resources management [10]. From a hydrological perspective, two main methods are generally used to simulate snowmelt: energy budget and temperature index methods. The energy budget method needs detailed observation data and a wide range of model parameters. The distribution of meteorological and hydrological stations in mountain basins is often limited, making it difficult to obtain and process the detailed information required for model study [11]. In contrast, the temperature index method uses air temperature as the only index of energy exchange at the snow surface [12]. The latter approach is commonly used in real-time hydrological forecasts. Examples of numerical models using the temperature index method include the National Weather Service River Forecast System model (1995), Streamflow Synthesis and Reservoir Regulation (SSARR) model, Hydrologic Engineering Center (HEC-1) model, Snowmelt Runoff Model for Windows (WinSRM), Cold Regions Hydrological Model (CRHM), Mesoscale Hydrologic Model (mHM), and the HEC–Hydrologic Modeling System (HEC-HMS) [13–17]. HEC-HMS model is a flexible hydrological model with particular physical significance designed to simulate a comprehensive range of hydrological processes coupled with a very sophisticated graphical user interface [18]. Modified melting rates have been used by many studies, using the hypothetical ATIMR (antecedent temperature index—melt rate) function used in the snowmelt module of HEC-HMS during calibration [19–22]; however, a commonly observed shortcoming in published literature is that no particular data is used to directly estimate the ATIMR curve. Therefore, its estimation and application to a mountainous basin with flow sources of complex composition is noteworthy here [23]. The method provided by Fazel et al. (2014) for one snowmelt period at distinct station locations was subsequently developed and applied by ¸Sengül and ˙Ispirli (2021) to create ATIMR curves specific to the Kırkgöze–Çipak Basin using hourly temperatures and snow–water equivalent (SWE) data using error analysis methods recommended by Bombardelli and García (2003) obtained from the three meteorology and snow observation stations [24–26]. Their results showed that the application of the ATIMR function using the observed data significantly improves the snowpack simulations, and it is quite useful for runoff simulations.

Although Turkey is a peninsula, it has a geography with an average altitude of over 1100 meters. Snowmelt runoff in the mountainous eastern part of Turkey is of great importance as it constitutes 60 to 70% in volume of the total yearly runoff during the spring and the early summer months [27]. Most of the annual water volumes in the dam reservoirs built in this region come from the precipitation in the winter months, snowmelt, and the rain falling on the snow cover in the spring. For this reason, conducting hydrological model studies based on snowmelt in the Eastern Anatolia Region of Turkey, where the snow potential is quite high, are of great importance both on a regional, national, and international scale in terms of the planning and economic management of water resources [25,27,28].

Advances in Geographic Information Systems and availability of geospatial databases have paved the way for estimation of several hydroclimatic variables. Reducing the uncertainties in these estimations made at various scales provides a better description of hydrological regimes [29,30]. bases have paved the way for estimation of several hydroclimatic variables. Reducing the uncertainties in these estimations made at various scales provides a better description of hydrological regimes [29,30]. In this study, which uses these advances in the availability of geospatial data, a con‐

Advances in Geographic Information Systems and availability of geospatial data‐

model studies based on snowmelt in the Eastern Anatolia Region of Turkey, where the snow potential is quite high, are of great importance both on a regional, national, and international scale in terms of the planning and economic management of water resources

In this study, which uses these advances in the availability of geospatial data, a continuous hydrological modeling approach is discussed by incorporating the soil moisture account (SMA) algorithm [31] with the snow accumulation and melting algorithm. The Hydrologic Engineering Center's Hydrologic Modeling System [18] was applied to the Kırkgöze–Çipak basin (Figure 1), considering the characteristic behaviors of point and areabased snow–water equivalent simulations by using the most sensitive ATIMR functions calculated on a physical basis [25], and the precipitation distribution algorithms embedded in the model were modified for depicting the actual watershed conditions. The development stages of the model, the determination of the parameters, and the calibration process are explained, and the model results are discussed. tinuous hydrological modeling approach is discussed by incorporating the soil moisture account (SMA) algorithm [31] with the snow accumulation and melting algorithm. The Hydrologic Engineering Center's Hydrologic Modeling System [18] was applied to the Kırkgöze–Çipak basin (Figure 1), considering the characteristic behaviors of point and area‐based snow–water equivalent simulations by using the most sensitive ATIMR func‐ tions calculated on a physical basis [25], and the precipitation distribution algorithms em‐ bedded in the model were modified for depicting the actual watershed conditions. The development stages of the model, the determination of the parameters, and the calibration process are explained, and the model results are discussed.

*Water* **2022**, *14*, x FOR PEER REVIEW 3 of 23

**Figure 1.** Study area and station locations. **Figure 1.** Study area and station locations.

#### **2. Materials and Methods 2. Materials and Methods**

#### *2.1. Area of Study*

[25,27,28].

*2.1. Area of Study* This study chose the Kırkgöze–Çipak Basin, located near the source of the Karasu Basin (Upper Euphrates Basin)—which is itself a sub‐basin of the Euphrates River—as the test area for this research. With an area of 242 km2 and altitude ranging from 1823 to 3140 m, the Kırkgöze–Çipak Basin is shown on the digital elevation model (DEM) in Figure 1. The median elevation of the basin is 2325 m, while the mean total basin slope is 15.3 de‐ grees. The geography comprises a rugged mountainous area with the main area being pas‐ ture and bare land. The characteristic climatological conditions are those of a cold, dry, and windy region. The region is covered by snow at least 150 days per year, and a signifi‐ cant part of the precipitation falls in the form of snow. The catchment area is not affected by urbanization or by reservoir regulation. Although the basin can be considered small in terms of scale, it has a large elevation difference that makes it possible to conduct snow modeling of major basins such as the Euphrates Basin. Previous snow studies in the area have shown how important snow dynamics and snow modeling are for this region [2,10,27,32–41]. The study area is located within the city center limits of Erzurum in This study chose the Kırkgöze–Çipak Basin, located near the source of the Karasu Basin (Upper Euphrates Basin)—which is itself a sub-basin of the Euphrates River—as the test area for this research. With an area of 242 km<sup>2</sup> and altitude ranging from 1823 to 3140 m, the Kırkgöze–Çipak Basin is shown on the digital elevation model (DEM) in Figure 1. The median elevation of the basin is 2325 m, while the mean total basin slope is 15.3 degrees. The geography comprises a rugged mountainous area with the main area being pasture and bare land. The characteristic climatological conditions are those of a cold, dry, and windy region. The region is covered by snow at least 150 days per year, and a significant part of the precipitation falls in the form of snow. The catchment area is not affected by urbanization or by reservoir regulation. Although the basin can be considered small in terms of scale, it has a large elevation difference that makes it possible to conduct snow modeling of major basins such as the Euphrates Basin. Previous snow studies in the area have shown how important snow dynamics and snow modeling are for this region [2,10,27,32–41]. The study area is located within the city center limits of Erzurum in Turkey, which is located at the intersection of Turkey's three major basins: the Çoruh, Aras, and Euphrates basins, and the snowmelt of the mountains in this region is the main source of water for these basins [3,42]. Therefore, the input parameters of the snowmelt model applied in this study will also be a good starting point for hydrological modeling studies of other mainstream resources in the vicinity.

The Kırkgöze–Çipak Basin includes a few state-built stations in its vicinity; however, these stations cannot provide enough information to effectively represent the pertinent spatial and temporal quality of the snowmelt-dominated basin. To compensate for this, three different automatic meteorology and snow observation stations that had been established in the Kırkgöze–Çipak Basin at the villages of Güngörmez and Kö¸sk, inside the grounds of a military radar location under a prior project numbered TÜB˙ITAK 106Y293, were developed over time. Station information is provided in Table 1 for each of the locations that are shown in Figure 1. This allowed climate data from stations in a mountainous basin with high snow potential to be collected in real time and of sufficient quality [35,36].



The upper levels of the study area are surrounded by basalts. These structures were formed as a result of numerous volcanic activities, so they show a complex structure that includes other volcanic rocks. The accumulated groundwater either discharges as small seasonal springs or is channeled to the adjacent formation comprising tuff and agglomerate (Figure 2). Tuff and agglomerate are common under basalts in this region. They were formed as a result of the cementation of angular pebbles of different size and blocks containing basalt, andesite, and tuff with fine-grained volcanic rocks.

The agglomerates, which are faulted and fractured in several directions, carry a small amount of groundwater in the fracture zones. In the region, tuff and agglomerate-inclusive claystone and marl layers are located due to the unconformity under the agglomerate. Many small seasonal springs are observed at the boundary of the clay and marl layer, which has a more impermeable structure than the formations above it [43].

**Automatic Meteorol‐ ogy and Snow Obser‐ vation Station**

**Figure 2.** (**a**) Geological map. (**b**) Land survey. (**c**) A–A' geological cross‐section of Kırkgöze–Çipak basin [44]**. Figure 2.** (**a**) Geological map. (**b**) Land survey. (**c**) A–A' geological cross-section of Kırkgöze–Çipak basin [44].

Turkey, which is located at the intersection of Turkey's three major basins: the Çoruh, Aras, and Euphrates basins, and the snowmelt of the mountains in this region is the main source of water for these basins [3,42]. Therefore, the input parameters of the snowmelt model applied in this study will also be a good starting point for hydrological modeling studies

The Kırkgöze–Çipak Basin includes a few state‐built stations in its vicinity; however, these stations cannot provide enough information to effectively represent the pertinent spatial and temporal quality of the snowmelt‐dominated basin. To compensate for this, three different automatic meteorology and snow observation stations that had been estab‐ lished in the Kırkgöze–Çipak Basin at the villages of Güngörmez and Köşk, inside the grounds of a military radar location under a prior project numbered TÜBİTAK 106Y293, were developed over time. Station information is provided in Table 1 for each of the loca‐ tions that are shown in Figure 1. This allowed climate data from stations in a mountainous basin with high snow potential to be collected in real time and of sufficient quality [35,36].

> **Average Slope of Land Close to the Station (Degrees)**

The upper levels of the study area are surrounded by basalts. These structures were formed as a result of numerous volcanic activities, so they show a complex structure that includes other volcanic rocks. The accumulated groundwater either discharges as small seasonal springs or is channeled to the adjacent formation comprising tuff and agglomer‐ ate (Figure 2). Tuff and agglomerate are common under basalts in this region. They were formed as a result of the cementation of angular pebbles of different size and blocks con‐

The agglomerates, which are faulted and fractured in several directions, carry a small amount of groundwaterin the fracture zones. In the region, tuff and agglomerate‐inclusive claystone and marl layers are located due to the unconformity under the agglomerate. Many small seasonal springs are observed at the boundary of the clay and marl layer,

**Simulation Time Interval**

of other mainstream resources in the vicinity.

**Table 1.** Parameters of the meteorology stations.

KÖŞK 2019 Northwest Dry Farming 9.90 10/22/2008–9/30/2011 GÜNGÖRMEZ 2454 Southeast Transition Area 24.10 10/22/2008–9/30/2011 RADAR 2891 Northwest Transition Area 12.06 10/22/2008–9/30/2011

taining basalt, andesite, and tuff with fine‐grained volcanic rocks.

which has a more impermeable structure than the formations above it [43].

**Altitude (m) Aspect Land Use**
