Introduction

Sustainable management of mountainous watersheds is one of the fundamental challenges in semi-arid regions of Iran. This management requires a deep and integrated understanding of the interactions between topographic landforms and the spatial distribution of climatic variables and vegetation cover. However, in many mountainous regions of Iran, particularly in watersheds with significant morphological diversity, integrated analysis and spatial modeling of these relationships have received less attention. Mountainous watersheds, due to their considerable elevational differences, typically exhibit significant variations in temperature, precipitation, and evaporation from lowlands to high elevations. This climatic diversity, in turn, affects vegetation distribution, landform types, soil erosion intensity, and ultimately ecosystem stability. The present study aimed to spatially model the effect of topographic parameters (elevation and slope) on the distribution of climatic variables (temperature, precipitation, and evaporation) and the Normalized Difference Vegetation Index (NDVI) in the watershed located northeast of Eqlid County. This region, situated on the eastern slopes of the central Zagros Mountains, exhibits considerable elevational diversity (ranging from approximately 2323 to 3842 meters above sea level) as well as notable climatic and vegetation variability, making it an ideal case study for such an investigation. The findings of this research can enhance the fundamental understanding of climate-geomorphology-vegetation interactions and provide a quantitative tool for management zoning of similar watersheds.

Method

To conduct this research, climatic data including mean annual temperature, annual precipitation, and annual evaporation were first collected from six active synoptic stations within and around the region (Abadeh, Eqlid, Kafter, Izadkhvast, Shahreza, and Sadeghabad stations) over a ten-year statistical period (2011–2021). After quality control and homogeneity assessment, the data were imported into a Geographic Information System (GIS) environment. To prepare continuous zoning maps of climatic variables across the entire watershed, the Kriging interpolation method was employed, with elevation incorporated as an auxiliary variable. This method was selected due to its ability to account for the spatial structure of the data and to provide lower estimation errors for the study area. To extract topographic parameters, a Digital Elevation Model (DEM) with a spatial resolution of 30 meters, derived from ASTER satellite data (2022), was prepared. From this model, a slope map (in percent) and an elevation class map (with 200-meter intervals) were generated. Furthermore, to classify the landforms of the region, the Topographic Position Index (TPI) was calculated at two scales: local (3×3 cell window) and regional (45×45 cell window). Based on TPI values and considering surface slope, ten landform types including narrow valleys, U-shaped valleys, plains, open slopes, mid-slope ridges, peaks, and ridgelines were identified in the region. For quantitative assessment of vegetation cover, a Landsat 8 OLI satellite image from 2015 was acquired, and necessary preprocessing steps including atmospheric correction (using the FLAASH method) and geometric correction (using ground control points with an error of less than 0.5 pixels) were applied. Subsequently, the Normalized Difference Vegetation Index (NDVI) was calculated using the red band (band 4) and the near-infrared band (band 5). Soil erosion intensity was also estimated using the empirical EPM (Gavrilović) model. Finally, spatial relationship analysis between topographic parameters and climatic variables was conducted using two complementary approaches: (1) extracting temperature, precipitation, and evaporation values for each elevation class and plotting the trend of variations, and (2) comparing climatic classes with elevation, slope, and landform classes through cross-tabulation analysis in the GIS environment.

Results

The findings of this study conclusively demonstrated that elevation, as the most important controlling topographic parameter, determines the spatial distribution of all three climatic variables (temperature, precipitation, and evaporation). With increasing elevation from the northern parts (2323 m) to the southern parts of the watershed (3842 m), mean annual temperature decreased from over 12°C to below 4°C. Annual precipitation showed an opposite trend, increasing from less than 250 mm in the northern lowlands to more than 650 mm in the southern high elevations. Evaporation also decreased predictably with increasing elevation; evaporation rates exceeded 7000 mm in the northern lowlands, while decreasing to less than 2000 mm at elevations above 3500 meters. The relationship between slope and climatic variables was more complex and non-linear. Analyses revealed that with increasing precipitation (corresponding with increasing elevation), slope values initially increased up to precipitation class 5 and then showed a relative decrease in higher classes (very high elevations). This pattern indicates the presence of relatively flat summit surfaces at very high elevations. Regarding landforms, results showed that with decreasing temperature and evaporation (i.e., moving toward higher elevations), landforms shifted from valleys and plains in the north (lower landform classes) toward peaks and ridges in the south (landform class 10). NDVI exhibited a parabolic relationship with temperature; maximum NDVI (0.49) was recorded at mid-elevations and relatively moderate temperatures (temperature classes 3 and 4), while in the coldest areas (elevations above 3800 meters with temperatures below 4°C), vegetation cover declined due to physiological limitations caused by cold, frost stress, and thin soils (NDVI approximately 0.10). Regarding erosion, results showed that with decreasing evaporation and temperature classes and with increasing precipitation classes, erosion intensity shifted from high and moderate classes to low classes.

Conclusions

This study conclusively demonstrated the existence of a strong and significant systemic relationship between topographic parameters (elevation and slope) and climatic variables (temperature, precipitation, and evaporation) in the northeast Eqlid watershed. Elevation, as the primary controlling factor, determines the distribution of temperature, precipitation, and evaporation, and these climatic variables in turn affect landform type, erosion intensity, and vegetation patterns. The non-linear relationship between slope and precipitation and the parabolic relationship between temperature and NDVI indicate the complexity of environmental interactions in mountainous watersheds and demonstrate that increased precipitation alone is not sufficient for vegetation development; temperature acts as a limiting factor at very high elevations. From a practical perspective, by accurately measuring topographic parameters (which can be readily extracted from digital elevation models), the spatial distribution of climatic variables can be estimated with acceptable accuracy in similar mountainous watersheds. Therefore, topography-based spatial modeling can serve as a powerful auxiliary tool in areas with limited meteorological station coverage.