Water balance and influence mechanism analysis: a case study of Hongjiannao Lake, China

Abstract

Hongjiannao groundwater exchange was the largest desert freshwater lake in China (57.25 km 2 in 1986). However, it shrank sharply over the past 34a (1986-2019), with the smallest lake area 31.41 km 2 in 2015. The objective of this study was to use the Landsat images, ASTER GDEM V2 data, and meteorology and statistics data, in combination with the water balance model to calculate the dynamics of water balance elements, quantify and characterize the interannual variations in lakegroundwater exchanges, and analyzed its influencing factors by using the geographical detector. The results showed that in the stable stage (1986-1997), the average rate of the lake area, water level, and lake volume change was-0.26 km 2 /a,-0.0483 m/a, and-0.0009 km 3 /a, respectively. Precipitation, river inflow, and groundwater were 0.0203 km 3 , 0.0485 km 3 , and 0.0098 km 3 , which accounts for the whole input were 25.83%, 61.70%, and 12.47%, respectively, evaporation was 0.0786 km 3. In the reduction stage (1998-2015), the average rate of the lake area, water level, and lake volume change was-1.21 km 2 /a,-0.2422 m/a, and-0.0101 km 3 /a, respectively. Before 2006, precipitation, river inflow, and groundwater were 0.0154 km 3 , 0.0475 km 3 , and-0.0025 km 3 , respectively; from 2006 to 2009, precipitation, river inflow, and groundwater were 0.0143 km 3 , 0.0334 km 3 , and 0.0058 km 3 , respectively; after 2009, precipitation, river inflow, and groundwater were 0.0139 km 3 , 0.0199 km 3 , and 0.0085 km 3 , respectively. Evaporation decreased from 0.0714 km 3 to 0.0480 km 3 from 1998 to 2015. In the growth stage (2016-2019), the average rate of the lake area, water level, and lake volume change were 1.38 km 2 /a, 0.27 m/a, and 0.0088 km 3 /a, respectively. Precipitation, river inflow, and groundwater were 0.0209 km 3 , 0.0005 km 3 , and 0.0373 km 3 , which accounts for the whole input were 46.63 %, 52.12 %, and 1.25 %, respectively, evaporation was 0.0187 km 3. Compared with the stable stage, groundwater in the growth stage reduced from 12.47 % (0.0098 km 3) to only 1.25 % (0.0005 km 3). From 1998 to 2004, Hongjiannao Lake experienced continuous losing conditions (discharge from the lake to groundwater), with a variable exchange volume of up to-0.01582 km 3 in 1999. Through geographical detector analysis, it was found that temperature was the dominant factor from 1988 to 1997, while human factors were the dominant factors from1998 to 2015.

Analysis of Detailed Lake Variations and Associated Hydrologic Driving Factors in a Semi-Arid Ungauged Closed Watershed

“…This study provides a valuable supplement to these previous studies and can address the gaps in simulating detailed hydrologic processes related to lakes. In the HJN watershed, previous studies identified precipitation and evaporation (or temperature) as the meteorological driving factors influencing lake variations [68][69][70], and surface runoff and evaporation were identified as the hydrologic driving factors [30]. These results were consistent with the annual mass balance in our study.…”

“…Previous studies have confirmed the effectiveness of utilizing remote-sensed ET data for model evaluation in such areas [42][43][44]. Based on the hydrological characteristics of lakes in semi-arid regions [13,30,58], in addition to the remote-sensed ET data, we also used remotely sensed lake areas and the results from previous studies for model evaluation. The calibration and validation results indicated that the simulated ET was between satisfactory and good in general and underestimation mainly occurred from July to October.…”

“…Most previous studies in semi-arid and ungauged closed watersheds used remotesensing data and water-balance models to analyze monthly and annual lake variations [25][26][27][28][29][30]. This study provides a valuable supplement to these previous studies and can address the gaps in simulating detailed hydrologic processes related to lakes.…”

“…Integrating remote-sensing data with hydrologic modeling is an effective method to simulate and predict continuous hydrologic processes under various climate conditions [25][26][27]. Compared with remote-sensing data alone, the combined method can depict the internal hydrologic processes between climate and lakes (e.g., surface runoff, groundwater flow, and snowmelt), and quantify the impacts of these processes on lake variations [28][29][30]. Many studies have been conducted to simulate the daily variations of lakes and their associated hydrologic processes with long time periods in gauged watersheds [31][32][33].…”

Spatiotemporal Variation of Groundwater Extraction Intensity Based on Geostatistics—Set Pair Analysis in Daxing District of Beijing, China

“…Some evaluation methods are used in developing and utilizing groundwater. These include the water balance method [18,19], numerical simulation method [20,21], isotope tracer method [22], principal component analysis, fuzzy comprehensive analysis, risk matrix method, projection pursuit method [23], and set pair analysis method [24,25]. Among these, set pair analysis can reflect the uncertainty relationship between evaluation indexes and evaluation standards from the three aspects of identity, difference, and opposition.…”