برآورد شار خالص آب سطحی و ارتباط آن با پارامتر های هیدرولوژیکی و اکولوژیکی در حوضه دریاچه ارومیه

شار آب خالص (nwf) به عنوان یک عامل مهم در حفظ تعادل هیدرولوژیکی در اکوسیستم‌های خشکی و تعیین نرخ تجدید مخازن آب زیرزمینی نقش دارد. در این تحقیق، از مدل تحلیلی و داده‌های رطوبت خاک سطحی ماهواره smap در بازه زمانی 2015 تا 2020 برای تخمین nwf در حوضه آبریز دریاچه ارومیه استفاده شده است. مدل تحلیلی مورد استفاده براساس معادله خطی شده ریچاردز تنظیم شده که دینامیک رطوبت خاک را تحت تاثیر جریان‌های آب نفوذی و گرانشی توضیح می‌دهد. این مدل امکان محاسبه شار آب خالص سطحی را از داده‌های رطوبت خاک فراهم می‌کند. نتایج به دست آمده حاکی از آن است که میانه nwf در حدود 0.5 سانتی‌متر در روز است و دامنه بین چارکی (iqr) معمولاً بین 0.5 تا 1.5 سانتی‌متر در روز قرار دارد. تحلیل همبستگی رابطه قابل توجهی بین nwf و متغیرهای محیطی مانند رطوبت خاک (همبستگی 0.57)، شاخص پوشش گیاهی (ndvi) (همبستگی 0.33-) و دمای سطح زمین (lst) (همبستگی 0.57-) را نشان می‌دهد. این تحقیق بر اهمیت مدیریت دقیق منابع آب در حوضه دریاچه ارومیه و استفاده از داده‌های ماهواره‌ای و ابزارهای مدل‌سازی برای تحلیل و مدیریت منابع آب تاکید دارد. این مطالعه نشان می‌دهد که درک دقیق از تعاملات بین پارامترهای هیدرولوژیکی و اکولوژیکی می‌تواند به تصمیم‌گیری‌های مدیریتی موثر برای حفاظت از منابع آب و اکوسیستم‌های مرتبط کمک کند.

estimation of surface net water flow and its relationship with hydrological and ecological parameters in the urmia lake basin

introductionthe dynamics of hydrological fluxes are integral to maintaining the delicate balance within the earth’s ecosystems. as the primary conduits of water, energy, and biogeochemical cycles, these fluxes not only support the fundamental processes of life but also act as critical indicators of environmental health and sustainability. the surface net water flux (nwf), a crucial parameter emerging from the interplay between infiltration and evapotranspiration, acts as a barometer for the underlying hydrological processes that dictate the recharge rates of vital groundwater reserves. the essence of understanding nwf lies in its direct correlation with the overall water availability within a region, which is instrumental for agricultural productivity, ecosystem vitality, and human consumption. in the face of expanding urbanization, intensive agricultural practices, and the unpredictable swings of climate change, the hydrological fluxes are subject to significant perturbations. these disruptions, often stemming from anthropogenic influences, have the potential to profoundly alter the natural cycles, thereby necessitating advanced methodologies for accurate monitoring and predictive modeling. while the impact of such changes might be localized in nature, their cumulative effect can have far-reaching implications for regional water security and ecological integrity (sadeghi et al., 2019). groundwater, the unseen treasure beneath our feet, is under increasing pressure as global populations soar and demands for water surge. this silent crisis of groundwater depletion, marked by falling water levels and deteriorating quality, poses one of the most significant challenges for contemporary water management (moore fisher, 2012; richey et al., 2015). studies have underlined the importance of robust monitoring systems, combining field data, remote sensing, and sophisticated modeling, as pivotal for diagnosing the health of our hydrological systems. the national research council (2012) has particularly emphasized the critical role of such integrated approaches in addressing water resource management’s vulnerabilities and challenges. in this study, we will dissect the mechanisms of nwf and its profound influence on the ecological and hydrological parameters within the urmia lake basin. materials and methods situated in northwest iran, the urmia lake basin spans approximately 51,801 square kilometers, surrounded by the northern zagros mountains, the southern slopes of mount sabalan, and the northern, western, and southern flanks of mount sahand. this diverse landscape features the sentinel lake urmia, positioned 1276 meters above sea level, covering about 5750 square kilometers and surrounded by 16 wetlands, illustrating the region’s ecological vulnerability. this study focuses on soil moisture dynamics using l4 data from the smap satellite, emphasizing its critical role in hydrological and climatic processes such as runoff, flood modeling, and drought monitoring. additional data from the chirps dataset and modis products enrich our understanding of the hydrological interactions within the basin, with groundwater volume derived from the gldas-2.2 product and water levels of lake urmia from local databases. the analytical model for estimating surface net water flux (nwf), developed by sadeghi et al. (2019), uses direct soil moisture data and applies warrick’s (1975) solution to richards’ equation (1931), which describes soil moisture dynamics due to infiltration and gravitational water flow in variably saturated soils. this model predicts nwf accurately without the need for calibration, providing a computational advantage and facilitating its application in environmental studies and water resource management.results and discussionthe results and discussion section of the research conducted on the urmia lake basin, spanning 2015 to early 2021, highlights significant fluctuations in the surface net water flux (nwf), suggesting a solid seasonal pattern influenced by the hydrological conditions of the basin. analyzing the temporal dynamics, periods of increased nwf correlate with rainy seasons, leading to heightened surface and subsurface water flows towards lake urmia, while decreases during dry seasons coincide with elevated evaporation and transpiration, reducing basin water inputs. the overall trend suggests that these variations do not follow a long-term increase or decrease but are predominantly driven by annual and seasonal factors. annual and seasonal box plots reveal stable medians amidst more comprehensive ranges of data variability across different years, with 2018 and 2020 marked by significant variability likely due to climatic or land-use changes. this period analysis underlines the nwf’s sensitivity to environmental and anthropogenic factors. the multifaceted analysis further includes a correlation heatmap showing solid relationships between vital environmental variables such as soil moisture, vegetation indices, and lake water levels, underscoring the interconnectedness of the ecosystem’s water dynamics. these insights are crucial for strategic water resource management and highlight the need for comprehensive data and consideration of water use policies to ensure informed decision-making. this analysis exemplifies how integrated data-driven approaches can enhance the understanding and managing of water resources in ecologically sensitive regions. conclusion in this study, after estimating the surface net water flux (nwf) in the urmia lake basin, we examined its impact on the hydrological and ecological parameters within the basin. utilizing soil moisture data from the smap satellite and the analytical model developed by sadeghi et al. (2019), the surface nwf was estimated from 2015 to 2020. the results indicated that the surface nwf, which results from the difference between infiltration and evapotranspiration, plays a crucial role in maintaining the water balance and, consequently, the water level of lake urmia. this study revealed that seasonal and annual variations in the surface nwf significantly affect soil moisture, precipitation, evaporation, and underground water storage. additionally, correlation analyses demonstrated significant relationships between the surface nwf and environmental parameters such as soil moisture, the normalized difference vegetation index (ndvi), and land surface temperature (lst). the analyses conducted on satellite data and hydrological models highlight that effective water resource management in the urmia lake basin requires a thorough understanding of the interactions between hydrological and ecological parameters. this understanding can lead to more effective management decisions to conserve water resources and associated ecosystems. ultimately, this study underscores the importance of utilizing satellite data and advanced models to analyze and manage water resources. given the increasing challenges posed by climate change and human activities, developing methods for sustainable study and management of water resources is essential to maintaining ecosystem balance and meeting the water needs of human communities.