In this paper, evapotranspiration (ET) and leaf area index (LAI) were used to calibrate the SWAT model, whereas remotely sensed precipitation and other climatic parameters were used as forcing data for the 6300 km² Day Basin, a tributary of the Red River in Vietnam. The efficacy of the Sequential Uncertainty Fitting (SUFI-2) parameter sensitivity and optimization model was tested with area specific remote sensing input parameters for every Hydrological Response Units (HRU), rather than with measurements of river flow representing a large set of HRUs, i.e., a bulk calibration. Simulated monthly ET correlations with remote sensing estimates showed an R² = 0.71, Nash–Sutcliffe Efficiency NSE = 0.65, and Kling Gupta Efficiency KGE = 0.80 while monthly LAI showed correlations of R² = 0.59, NSE = 0.57 and KGE = 0.83 over a five-year validation period. Accumulated modelled ET over the 5-year calibration period amounted to 5713 mm compared to 6015 mm of remotely sensed ET, yielding a difference of 302 mm (5.3%). The monthly flow at two flow measurement stations were adequately estimated (R² = 0.78 and 0.55, NSE = 0.71 and 0.63, KGE = 0.59 and 0.75 for Phu Ly and Ninh Binh, respectively). This outcome demonstrates the capability of SWAT model to obtain spatial and accurate simulation of eco-hydrological processes, also when rivers are ungauged and the water withdrawal system is complex.

Hydrological ecosystem services (HESS) describe the benefits of water for multiple purposes with an emphasis on environmental values. The value of HESS is often not realized because primary benefits (e.g., food production, water withdrawals) get the most attention. Secondary benefits such as water storage, purification or midday temperature cooling are often overlooked. This results in an incorrect evaluation of beneficial water usage in urban and rural resettlements and misunderstandings when land use changes are introduced. The objective of this paper is to propose a standard list of 17 HESS indicators that are in line with the policy and philosophy of the Consultative Group of International Agricultural Research (CGIAR) and that are measurable with earth observation technologies in conjunction with GIS and hydrological models. The HESS17 framework considered indicators that can be directly related to water flows, water fluxes and water stocks; they have a natural characteristic with minimal anthropogenic influence and must be quantifiable by means of earth observation models in combination with GIS and hydrological models. The introduction of a HESS framework is less meaningful without proper quantification procedures in place. Because of the widely diverging management options, the role of water should be categorized as (i) consumptive use (i.e., evapotranspiration and dry matter production) and (ii) non-consumptive use (stream flow, recharge, water storage). Governments and responsible agencies for integrated water management should recognize the need to include HESS17 in water allocation policies, water foot-printing, water accounting, transboundary water management, food security purposes and spatial land-use planning processes. The proposed HESS17 framework and associated methods can be used to evaluate land, soil and water conservation programs. This paper presents a framework that is non-exhaustive but can be realistically computed and applicable across spatial scales.

Distributed hydrological models are usually calibrated against the measured outflow of a certain drainage area, provided flow data is available. A close match with flow does however not mean that the spatially distributed hydrological processes are properly understood and simulated. In this paper, remotely sensed precipitation, evapotranspiration (ET) and leaf area index (LAI) from open access data sources were used to calibrate the SWAT model for the Day Basin, a tributary of the Red River in Vietnam. The efficacy of the SWAT-CUP parameter sensitivity and optimization model developed by Abbaspour (2015) was tested with spatial remote sensing input parameters. The innovation is that the parameters of the soil-vegetation processes were optimized for every Hydrological Response Unit for which remotely sensed monthly ET and LAI values were available. Such level of detail cannot be achieved from flow measurements, which are the integrated result of many processes over large areas. A total of 15 soil-vegetation process parameters were calibrated. The SUFI2 algorithm in SWAT-CUP appeared to be an adequate practical tool for the calibration process. Simulated monthly ET correlations with remote sensing estimates showed an R² = 0.71 and NSE = 0.65 while monthly LAI showed correlations of R² = 0.59 and NSE = 0.57 over a five year validation period. Accumulated modelled ET over the 5-year calibration period amounted to 5713 mm compared to 6015 mm of remotely sensed ET: a non-significant difference of 302 mm (5.3 %). Because river flow was not optimized during the calibration process, it could be used as an independent validation of the calibrated model simulations. The monthly flow at two flow measurement stations were adequately estimated (R² = 0.78 and 0.55, NSE = 0.71 and 0.63 for Phu Ly and Ninh Binh, respectively). The estimated total water withdrawal from the Red River was 1.934 billion m³/yr with a peak flow of approximately 200 m³/s during the months of February and July. The availability of a reliable set of parameters will make SWAT a useful tool for optimizing water conservation, agricultural outputs, and ecosystem services such as reduced soil erosion, better water quality standards, carbon sequestration, micro-climate cooling amongst others. Such calibrated distributed eco-hydrological models can be used for appraising scenarios of green growth.

The principles of Integrated Water Resources Management (IWRM), conservation of natural capital, and water accounting requires Hydrological Eco-System Services (HESS) to be determined. This paper presents a modeling approach for quantifying the HESS framework using the Soil Water Assessment Tool (SWAT). SWAT was used–after calibration against remote sensing data–to quantify and spatially identify total runoff, natural livestock feed production, fuelwood from natural forests, dry season flow, groundwater recharge, root zone storage for carrying over water from wet to dry season, sustaining rainfall, peak flow attenuation, carbon sequestration, microclimate cooling, and meeting environmental flow requirements. The environmental value of the current land use and vegetation was made explicit by carrying out parallel simulations for bare soil and vegetation conditions and reporting the incremental ecosystem services. Geographical areas with more and fewer HESS are identified. The spatial and temporal variability of annual HESS services is demonstrated for the Day Basin—which is part of the Red River delta (Vietnam)—for the period 2003 to 2013. The result shows that even though the basin is abundant with HESS, e.g., 7482 m³/ha of runoff, 3820 m³/ha of groundwater recharge, the trend for many HESS values, e.g., micro-climate cooling, meeting environmental flow requirements, and rootzone storage, are declining. It is found and proven that quantified HESS indicators highlighted the provisioning and regulating characters of ecosystem services, as well as geographical hotspots across the basin. The SWAT model shows the capability of simulating terrestrial eco-hydrological processes such as climate, soil, and current land use. The methodology illustrates how eco-hydrologists can benchmark ecosystem values and include HESS in exploring river basin management scenarios, climate change studies, and land use planning.