2.1. Study area description
The Helmand is the longest river in Afghanistan and the primary watershed for the endorheic Sistan Basin. This position is due to its location in the sub-desert environment and receiving low annual downpour. Fig.1 The basin is located between latitudes 29° 18′ to 34° 48′ and longitudes 60° 18′ and 69° 36′. The basin covers the central, southern and southwestern provinces of Afghanistan. Its total area is approximately 340,000 square kilometers, covering approximately 52% of Afghanistan, 31% of agricultural land and 28% of the Afghan population. The Basin is bordered by Iran to the west and Pakistan to the south.
The aquifers in the Helmand River Basin are generally of two types: consolidated layers and porous non-consolidated. The upper parts of the basin are mainly composed of solid rocks, and the lower parts consist of sedimentary rocks (Vincent et al. 2003).
Fig. 2. The graph shows the climate parameters of the HRB, prepared by employing GLDAS model remote sensing data. Based on the graph, the average temperature is 18 degrees Celsius, and the annual rainfall is 190 mm per year.
2.2. Data collection and processing
The Total Water Storage (TWS) is the sum of all above and below surface water storages, including canopy water, rivers and lakes, soil moisture and groundwater, and it represents a synthetic proxy of the dynamic of slow-responding hydrological quantities. According to previous studies, groundwater anomalies and soil moisture play the main role in these variations, and changes in snowmelt and glaciation have little effect on these changes (Khaki et al. 2018). Since the precipitation range in the HRB is from 50 to 250 mm per year, and the evaporation rate is high, it has virtually no snow and glaciers; thus, the influential parameters in water changes come from variations in soil moisture and groundwater. In general, principal changes in water storage (TWS) are equivalent to the sum of changes in groundwater (GW), changes in soil moisture (SM), changes in surface water (SW), and water changes equivalent to snow and glacier (SWE), and changes in the biosphere (BIO).
In this study, changes in the biosphere, water equivalent to snow, and glaciers are excluded due to their small size. As a result, the changes in groundwater are computed (Bonsor et al. 2010).
In the end according to the Fig.3, the results obtained from the above method have been compared and validated with monitoring data wells. Since there are no regular monitoring wells in the HRB, the outcomes are compared with recently established monitoring wells in some areas for their better accuracy.
2.3. Total Water Storage (TWS) Data Collection and Processing from GRACE and GRACE-FO Level-1
In this study, the first level GRACE satellite data from CSR[1] and JPL[2] data processing center were employed from January 2003 to July 2021. The first level TWS data is available at no cost in the platform (https://grace.jpl.nasa.gov/data- analysis-tool / ). The HRB CSR and JPL data (19×19) have some time irregularities for several months. One of the pros of GRACE satellite data is its complete spatio-temporal data over a large area provision. Also, despite its low resolution, it has the advantage of recording changes in total or part TWS water storage (BhanjaS, et al., 2016). In this work, TWS Roster data was converted to point data by utilizing Geographic Information System (GIS) software, then Point data was interpolated twice and consequently downscaled.
2.4. Global Land Data Assimilation System (GLDAS) data collection and processing
Since soil moisture, surface water, and water equivalent to snow and glaciers are integral elements in computing changes in groundwater storage, and albeit the accurate measurement of these parameters, obtaining these data in spacious areas is challenging. As a result, global GLDAS large-scale hydrological changes are better than other devices. The GLDAS NASA aims to employ advanced surface modeling and data correlation methods to capture satellite and terrestrial observational data outcomes to generate flow fields and optimize ground surface conditions (Rodell, 2009). In this paper, The GLDAS model soil moisture to a depth of 2 meters with surface water and the FLDAS[3] model, both with one-degree accuracy and the amount of water storage in plants, plus water equivalent to snow, is used. The data is available in this open source: (https://giovanni.gsfc.nasa.gov/giovanni/).
2.5 In-situ groundwater table measurements and aquifer characteristics
In the HRB, there is insufficient groundwater monitoring data. DACAAR is the only organization that has done some research in this field. Only between 1992 and 2011 has recorded groundwater level data irregularly (DACAAR, 2010). Since 2019 groundwater monitoring data has resumed in urban centers of southern provinces of Afghanistan. Due to the lack of regular and monthly monitoring well data in the HRB, groundwater monitoring data of DACAAR organization and MEW from 2003 to 2021, are employed to analyze the annual average groundwater table changes, and then compared with the annual average changes of the GRACE satellite groundwater. Groundwater reserves changes are determined utilizing monitoring well data by the following formula:
Groundwater level changes in monitoring wells (hswl) are equal to the difference in static groundwater levels in a time interval. Since the above data had a timing irregularity, the unknown numbers were derived using the linear interpolation method. (Sy) The confined aquifer special discharge is one of the geological characteristics of the region. Owing to the lack of special discharge data in this area, we have determined the average of specific discharge based on the type of aquifer types, and according to research conducted on different types of rocks, special discharge is as follows (Table1.)
Table 1. Specific yields of different geologic formations in the HRB (Jonson, 1992; US Army Corps, 2009)
No.
|
Type of aquifers
|
Sy range
|
Mean Sy in the HRB)
|
1
|
Unconsolidated sedimentary aquifers
|
0.01 to 0.28
|
0.07
|
2
|
Consolidated sedimentary rocks (sandstone, conglomerate, siltstone)/aquifers
|
0.01 to 0.10
|
0.035
|
3
|
Consolidated sedimentary rock (limestone) / aquifers
|
0.03 to 0.26
|
0.058
|
4
|
Bedrock/aquifers
|
0.0 to 0.005
|
0.0025
|
Based on the geological profiles of Kandahar Plain, and lithological logs of wells drilled in the Lashkar Gah region, revealing the unconfined aquifer beds consist of loams, having mud, sand and silt (Shroder, et al. 2016). In addition, according to the permeability tests of exploration boreholes being drilled in Kamal Khan Dam, Nimroz province, the results indicate a specific yield of 4.5% (MEW and SCGC, 2019). Based on geological map of the study area, the upper parts of the basin are composed of magmatic rocks, and the lower parts consist of sediments. The following formula obtains the average discharge for unconfined beds:
In this equation, Si is the specific discharge of the 1st aquifer bed, and Ai is the area of the 1st aquifer bed. Fig4. Illustrates the types of aquifers in the HRB. And based on this map, the main part of the area consists of loams with sediments accumulating in the lower parts of the basin, and the upper parts of the basin composed of consolidated sediments and bedrocks. Therefore, according to aforementioned description, 5.5% was assigned as an average specific yield of the formations for the whole basin.