Estimating surface water and vadose water resources for an ungauged inland catchment in Vietnam

This study aimed to assess water resources for the La Vi catchment, an ungauged inland basin in Vietnam. An Internet of Things-based automatic meteorological station has been installed in the catchment to record hourly weather data from 2016. By comparing water level observations with limited discharge measurements, discharges from November 2015 to February 2018 were calculated at Tan Hoa bridge using the slope-area method. The Soil and Water Assessment Tool was calibrated and validated for the wet season of 2015 and 2017, respectively, using the previously calculated water discharges. Statistical measures including Nash–Sutcliffe index, percent bias, and coefficient of determination indicated the satisfactory performance of the model in simulating water discharge on daily time steps during both periods. The results of the water resources assessment in the catchment showed that the annual average of blue water flow, green water flow, and green water storage reached 1,596.50, 371.13, and 15.36 mm, respectively. The blue water flow reached a higher value in the center of the catchment. Meanwhile, the high-value areas of green water flow and green water storage were in the western upstream and the riverside downstream. These findings could provide a valuable scientific foundation for sustainable watershed management.


INTRODUCTION
River discharge, the volume of water passes through a river cross section per unit of time, is a spatiotemporal output of the regional hydrologic cycle. Because river flow is generally concentrated in channels, discharge can be measured with more accuracy and precision than precipitation, evapotranspiration, or any other component of the hydrologic cycle (Dingman & Bjerklie ). For these reasons, measurements of river discharge not only provide direct information about climate, water resource availability, and flood hazards but also make invaluable data for validating the hydrologic models that are the useful means of forecasting the impacts of land use and climate change on water resources.
Methods of measuring streamflow generally fall into four categories (Gordon et al. ): (1) volumetric measurement, (2) velocity-area methods involving some measure of average stream velocity and cross-sectional area, (3) dilution gauging methods using a salt or dye, and (4)

Study area
The La Vi catchment, a tributary of the Kone river basin, is

Agriculture is the dominant economic activity of the La
Vi catchment with the area of agricultural land accounting for around 40%. In the structure of agricultural production, cultivation plays a key role with the main crops including Most people are concentrated in the East and North of the catchment.

Slope-area method
The slope-area method is used where there have not been measurements of discharge to provide a rating curve (Fenton & Keller  where Q is the discharge (m 3 /s), n is Manning's roughness (s/m 1/3 ), A is the cross-sectional area of the flow perpendicular to the flow direction (m 2 ), R is the hydraulic radius (m) ¼ A/P with P is the wetted perimeter of cross-sectional flow area (m) and S is the bottom slope of channel, m/m (dimensionless).
For the method to be valid, a reach must be carefully selected such that uniform flow conditions are approximated (Gordon et al. ). This means that the width and depth of flow, the water velocity, the streambed materials, and the channel slope remain constant over a straight reach, and further, that the channel slope and water slope are parallel. A straight, fairly homogeneous reach should be selected with a length at least five times the mean width (Dackombe & Gardiner ). Surveyed information is used to calculate the values of A and R. The slope, S, is actually the slope of the energy line. However, in practice, the energy slope is assumed parallel to the water surface slope and the bed slope. The more closely the reach approximates uniform conditions, the better the results. The last variable is Manning's n, which is a composite factor that accounts for the effects of many forms of flow resistance.
In a reach where the slope is uniform and the roughness of the bed and banks is similar (e.g., an artificial channel), Manning's n can usually be assumed to be a constant.
where SW t is the final soil water content (mm), SW o is the initial soil water content on day i (mm), t is the time (days), R day is the amount of precipitation on day i (mm), Q surf is the amount of surface runoff on day i (mm), E a is the amount of evapotranspiration on day i (mm), w seep is the amount of water entering the vadose zone from the soil profile on day i (mm), and Q gw is the amount of groundwater runoff on day i (mm).

Methodology
The implementation process of the study was divided into four parts (see Figure 2): (1) collecting weather data by IoT-based automatic meteorological station, rainfall gauge, and surface meteorological station, (2) calculating discharge in the La Vi catchment based on river morphology data, water level data, and discharge measurements using the slope-area method, (3)  The performance of the slope-area method and SWAT model in simulating discharge was evaluated by using three statistics quantitative indices, including Nash-Sutcliffe index (NSI), percent bias (PBIAS), and coefficient of determination (R 2 ). The performance ratings for these indices are shown in Table 1.

Data acquisition
The input data, including discharge, water level, weather, river morphology, topographic map, 2015 land-use map, and soil map, were collected from many different sources.
A detailed description of input data is shown in Table 2.   a DHT11 sensor to monitor air temperature, relative humidity, and a raindrop sensor to detect rainfall. All sensors were connected to an Arduino Uno, which was the main processing unit for the entire system. In turn, Arduino Uno retrieved, analyzed, and observed data from the sensors.
The processed data were then uploaded and stored in a website using NodeMCU and Ubidots. At the same time, the study collected daily rainfall data at the Phu Cat station provided by South Central Hydro-Meteorological Centre during the period from 1998 to 2017. In addition, the study also used daily weather data including air temperature, relative  method. The optimization model may be written as follows: Maximize, where Q s is the estimated discharge from water level data measured by pressure transducers using Equation (1)  August), and 2018 (31 January-9 February). The estimated discharges by the slope-area method in the above stages were discarded and not used to calibrate and validate the SWAT model.

Calibration and validation of the SWAT model
Based on the performance of the SWAT model in simulating daily discharge at the upstream side of Tan Hoa bridge (see Figure 5) and the guidelines summarized by Abbaspour et al.
(), nine relevant parameters were selected for model calibration as in Table 3. Figures 6 and 7  respectively. In addition, the green water coefficient was used to account for the relative importance of blue water  Note: r_ means the existing parameter value is multiplied by (1þ a given value), t-stat provides a measure of sensitivity (larger absolute values are more sensitive), and p-value determined the significance of the sensitivity (a value close to zero has more significance).
flow and green water flow, which is defined as the ratio of green water flow to the total green and blue water flows  For green water storage, the value ranged between 12 and 27 mm/year. However, there was a contrast between the central region and other areas of the catchment. High green water storage concentrated in the east and west.
Meanwhile in the central region, green water storage was low.
Considering its relative importance, the green water flow contributed less than a quarter of the total flow, except for a few sub-catchments near the downstream catchment. The value of green water coefficient was mainly in the range of 0.17-0.20.

DISCUSSION
The La Vi catchment has a long dry season that is identical to a semi-arid area. Two dominant soil types in the catchment are Haplic Acrisols and Rhodic Acrisols with soil texture of sand, loamy sand, or sandy loam, which has low  runoff potential and high infiltration rates. This leads to a strong contrast of natural streamflow between non-flood and flood seasons. In general, the peak flow of two seasons varies about 70 times. This result shows that people in the basin are exposed annually to water-related disasters such as droughts and floods.
The operation of Cay Tram weir located downstream is an effective structural solution that contributes to reducing droughts and floods. In the dry season, it prevents seawater intrusion, regulates irrigation water for agricultural production, and stabilizes groundwater for domestic needs.
Moreover, it drains floods quickly in the wet season.
Water resources in the basin are mainly contributed by blue water flow with more than 70% and concentrated dis- Besides, we use a systematic approach to separately analyze the two components of water resources as blue water and green water in terms of space and time. Since then, identifying emerging water issues, analyzing existing solutions, and proposing feasible solutions can enable sustainable use of water resources in the catchment. The above approach was implemented through SWAT, a semi-distributed and free-ofcharge model that has been used in Vietnam.
Limitations of this study are related to SWAT. Firstly, we have not been able to accurately restore streamflow when Cay Tram weir was operating. The reason is that SWAT is a one-dimensional hydrological model, not suitable for areas affected by tides or surges due to weirs. To overcome this limitation, hydraulic models could be integrated. In addition, because SWAT is a continuous model, it needs to be calibrated and validated for the long term in order to improve model performance. This could be done by using evapotranspiration and crop yield of remote sensing data.
Finally, this study has not considered groundwater in the saturated zone, an important water source during the dry season in the catchment. Therefore, further research should couple MODFLOW and SWAT to enhance the simulation ability of water resources in the catchment.

CONCLUSIONS
Quantifying water resources is a major challenge for hydrol- The study contributes insights into the flow regime and water budget in the La Vi catchment at both spatial and temporal scales. It could provide significant information for efficiently utilizing and allocating the water resources as well as sustainable agricultural development in the region.
The calibrated SWAT model in this study provides a strong basis for forthcoming studies in the catchment regarding agricultural land use change, climate change impact, and irrigation system planning.
The limitations of this study are related to the SWAT model nature and availability of the input data. To overcome these challenges, it is necessary to integrate the SWAT model with hydraulic models, groundwater models and exploit remote sensing data.