**1. Introduction**

Dams are intended to offer substantial aid to humankind by ensuring an enhanced water availability for municipal, industrial, and agricultural uses, as well as increased capability of flood regulation and hydropower generation [1]. On the other hand, the construction of dams has considerably changed the natural flow regime of rivers worldwide. Above half of the 292 large river systems in the world have been affected by dams [2,3]. The influence of human activities in altering river discharge has profoundly increased in recent decades [4]. Over an intermediate time scale (e.g., decadal scale), human interferences in terms of water consumption, land-use change, dam construction, and sand mining, among others, are the powerful factors that escalate basin-scale hydrological changes. Therefore, a site-specific study is needed to disclose the governing effects of human disruptions on these hydrological changes [5–7].

To temper river floods, reduce water collection for irrigation, hydropower generation and facilitate navigation, dams have been created across big rivers around the world [8]. Dams have grown to one of the most perturbing human intrusions in river systems as the

*Article*

**Citation:** Yasir, M.; Hu, T.; Abdul Hakeem, S. Impending Hydrological Regime of Lhasa River as Subjected to Hydraulic Interventions—A SWAT Model Manifestation. *Remote Sens.* **2021**, *13*, 1382. https://doi.org/ 10.3390/rs13071382

Academic Editors: Luca Brocca, Carl Legleiter and Yongqiang Zhang

Received: 4 February 2021 Accepted: 31 March 2021 Published: 3 April 2021

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**Copyright:** © 2021 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/).

number of dams and the total storage capacity of reservoirs rapidly increase [4]. Therefore, knowledge of dam construction and its regulating effects on river discharge is crucial for river and delta managemen<sup>t</sup> and restoration. Highly regulated rivers in China are subject to large-scale ecosystem amendments made by hydrological alterations. Many of the earlier studies related to dam-induced hydrological alterations across river basins in China focused on the impacts of large dams that generally aim to control floods in large basins, such as the Lancang River [9], the Mekong River [10], the Pearl River [11], the Yangtze River [12], and the Yellow River [13,14]. In addition to large dams, the development of small dams has also been highlighted in national energy policies in China [15]. Therefore, small dam construction is intense in China, especially in South China, where hydropower resources are extensive. Thus, to fill in the knowledge void, the present study focused on the impact appraisal of reservoir functioning in the Lhasa River Basin, a Qinghai–Tibetan Plateau basin in South China (for more information, see Section 2.2). Several researchers have established a number of approaches with the objective of reckoning of the hydrologic modifications caused by human activity. However, hydrological modeling can be an effective alternative for hydrological analysis in different scenarios [16]. The SWAT (Soil and Water Assessment Tool) model developed by the authors of [17] has already been in widespread use for water resource managemen<sup>t</sup> in many different rivers [18–23]. Additionally, there has been a general lack of applications of physically-based hydrological models to the Yarlung Tsangbo River Basin, especially the Lhasa River Basin [24]. The SWAT model was applied to the Lhasa River Basin in a recent study [25], where streamflow and sediment load were predicted for the Lhasa River in future. The SWAT model was applied to the Lhasa River Basin to simulate its streamflow variability under reservoir influence [26]. The SWAT model was utilized in [27] for hydrological drought propagation in the South China Dongjiang River Basin using the "simulated–observed approach". Their study estimated the effects of human regulations on hydrological drought from the perspective of the development and recovery processes using the SWAT model.

Streamflow forecasting is of grea<sup>t</sup> significance to water resource managemen<sup>t</sup> and planning. Medium-to-long-term forecasting including weekly, monthly, seasonal, and even annual time scales is predominantly beneficial in reservoir operations and irrigation management, as well as the institutional and legal features of water resource managemen<sup>t</sup> and planning. Due to their reputation, a large number of forecasting models have been developed for streamflow forecasting, including concept-based, process-driven models such as the low flow recession model, rainfall–runoff models, and statistics-based datadriven models such as regression models, time series models, artificial neural network models, fuzzy logic models, and the nearest neighbor model [28]. Of various streamflow forecasting methods, time series analysis has been most widely used in the previous decades because of its forecasting capability, inclusion of richer information, and more systematic way of building models in three modeling stages (identification, estimation, and diagnostic check), as standardized by Box and Jenkins (1976) [29]. The current study made use of "simulated–observed approach" after [27] for predicting the Lhasa River streamflow under reservoir operations in the Lhasa River Basin. SWAT-simulated and observed hydrological time series were used introduced to a stochastic AutoRegressive Integrated Moving Average (ARIMA) model. As a common data-driven method, the ARIMA model has been widely used in time series prediction due to its simplicity and effectiveness [30]. Adhikary et al. (2012) [31] used seasonal ARIMA (SARIMA) model to model a groundwater table. They took weekly time series and concluded that SARIMA stochastic models can be applied for ground water level variations. Valipour et al. (2013) [32] modeled the inflow of the Dez dam reservoir with SARIMA and ARMIA stochastic models. His research results showed that the SARIMA model yielded better results than the ARIMA model. Ahlert and Mehta (1981) [33] analyzed the stochastic process of flow data for the Delaware River by the ARIMA model. Yurekli et al. (2005) [34] applied SARIMA stochastic models to model the monthly streamflow data of the Kelkit River. Modarres and Ouarda (2013) [35] demonstrated the heteroscedasticity of streamflow time series with the ARIMA model

in comparison to GARCH (Generalized Autoregressive Conditionally Heteroscedastic) models. Their results showed that ARIMA models performed better than GARCH models. Ahmad et al. (2001) [36] used the ARIMA model to analyze water quality data. Kurunç et al. (2005) [37] used the ARIMA and Thomas Fiering stochastic approach to forecast streamflow data of the Yesilurmah River. Tayyab et al. (2016) [38] used an auto regressive model in comparison to neural networks to predict streamflow.

The current study primarily aimed to (i) investigate the reservoir operations' impact on the Lhasa River discharge, (ii) apply the SWAT model to simulate Lhasa River streamflow under multiple reservoir functioning, and (iii) to predict Lhasa River streamflow under reservoir's influence using 'observed' and 'SWAT-simulated' hydrological data series as a step forward in overcoming the data scarcity problem of the area. The study was intended to benefit water resource managers and hydrological engineers in understanding the future hydrological regime in the Lhasa River Basin under reservoir functioning and aiding in developing better managemen<sup>t</sup> practices and planning for hydrological resources in the area. The current study holds novelty in combining a physical-based hydrological model and a statistical time series forecasting model for the simulation and prediction, of the discharge of the Lhasa River respectively, one of the important rivers in the datascarce Qinghai–Tibetan Plateau, which is under the influence of recent major hydraulic interventions in the form of the Zhikong and Pangduo hydropower reservoirs.

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

#### *2.1. Study Area—Lhasa River Basin*

The Lhasa River Basin (LRB), ranging from 29◦19 to 31◦15N and from 90◦60 to 93◦20E, is the economical and authoritative hub of the autonomous Qinghai–Tibetan plateau (QTP). The Lhasa River (LR) is the longest tributary of the Yarlung Tsangpo River; LRB covers a ≈32,321 km<sup>2</sup> basin area (ArcSWAT-estimated area by the digital elevation model used in the current study), comprising 13.5% of the total area of the Yarlung Tsangpo basin [39]. The LRB exhibits typical semi-arid monsoonal climate conditions, where the major proportion of received rainfall is concentrated in the summer season from June to September with the simultaneous generation of peak LR discharge during the same time. Peng et al. (2015) [24] showed that rainfall in summer is a governing feature in producing summer stream flow in the Lhasa River basin. Thus, the rainfall disproportion poses a direct influence on the rainfall-dependent runoff generation phenomena in the basin. The hydrometric and meteorological records for the LRB are maintained at the Pondo, Tanggya, and Lhasa hydrometric stations and the Damxung, Maizhokunggar, and Lhasa meteorological stations, respectively.

The LR stretches to a length of 551 km with a hydropower potential of 1.177 million kWh [39], and it is substantial in fulfilling the hydropower and agricultural requirements of the local community. The LR has been exposed to major hydraulic interventions in the form of reservoir development and confinement during the last and present decades. It is of vital importance to understand the hydrological phenomena of the LRB under the influence of hydraulic structures for a better understanding of the hydrological behavior of the study area to facilitate the understanding of future water resource availability and managemen<sup>t</sup> in the area. The major hydraulic developments in the study area are the installation of Zhikong and Pangduo hydropower stations over the LR.

#### Zhikong and Pangduo Reservoirs Impoundment on Lhasa River

The Zhikong and Pangduo Dams were built in 2006 and 2013, respectively, on the LR. The Zhikong Dam is located 96 km upstream the urban Lhasa city in the middle and lower reaches of the LR, and it is 65 km downstream the Pangduo Dam, thus impounding the upper LR. To meet the substantially increasing power demand of the Tibet plateau, the Zhikong Dam was built with an installed power capacity of 100 MW and a reservoir water storage capacity of 0.225 billion m3. The other purposes of this installation include flood control in high rainfall months and irrigation water supply in low rainfall spells during

the year. However, Wu et al. (2018) [39] showed that impoundment by the Zhikong Dam unswervingly altered the hydrological behavior of the downstream channels of the LR. The succeeding major hydrological intervention on the LR was the construction of the Pangduo Dam with 160 MW of installed capacity and 1.23 billion m<sup>3</sup> of reservoir water storage capacity. The development purposes of the Pangduo water conservancy project include irrigation water availability, power generation, and flood control. It is the pillar project and a leading reservoir developed for the enormous growth of the LRB.
