Watershed-scale Models Research Articles

Computationally efficient Watershed-Scale hydrological Modeling: Integrating HYDRUS-1D and KINEROS2 for coupled Surface-Subsurface analysis

Watershed flow processes consist of partitioning, movement, storage, and redistribution of water fluxes in space and time. However, the integrated modeling of these processes is challenging due to computational burden, extensive data requirements, and/or reliance on simplifying assumptions. This study introduces a novel and computationally efficient modeling framework that leverages two state-of-the-art process-based models: HYDRUS-1D (H1D) for unsaturated flow and KINEROS2 (K2) for overland flow. The framework extends a hillslope-scale coupled H1D-K2 model to simulate watershed-scale processes, where H1D replaces the three-parameter Parlange’s infiltration equation in the event-based K2 model. Boundary condition switching is employed to account for surface ponding and water exchange between the two model domains. The structure of the coupled watershed-scale H1D-K2 model consists of a cascade of connected rectangular planes, channel elements, and 1D soil profiles to simulate 1D overland flow, infiltration, unsaturated zone flow, and recharge. Computational efficiency relative to HYDRUS-2D is achieved through a dynamic time-stepping approach and dimensionality reduction. The watershed scale model improved the computational time by 14.3% and 47% compared to the corresponding Hillslope scale H1D-K2 and HYDRUS-2D, respectively. The performance and efficiency of the new watershed model are demonstrated using benchmark watershed and/or hillslope simulations. Calibrated hydrographs and water balance components using Walnut Gulch Experimental Watershed data, showed excellent agreement with observed data with a Nash-Sutcliffe coefficient (NSC) greator than 0.8 and Pearson correlation coefficient (R2) greater than 0.92.

Sustainable Watershed Management: Assessing the Impact of Data Precision on Sediment Transport in the Oostanaula Creek Watershed, Tennessee

This study applies the WaTEM/SEDEM model, a watershed-scale model based on the Universal Soil Loss Equation (USLE), to enhance sustainable watershed management by identifying high-erosion-risk areas for targeted mitigation at various scales. It focuses on identifying potential errors in using statewide or worldwide land use data layers derived from remote-sensing algorithms and inaccuracies in the spatial distribution of cropland and soil types resulting in misinterpretation of sediment yields. These model limitations emphasize the need for field validation and precise input data, particularly stream data, to improve the reliability of these models. The study examines hydrologic rainfall-runoff processes in Tennessee’s 182 km2 Oostanaula catchment using various data sources, including the National Land Cover Database (NLCD), the European Space Agency WorldCover dataset (ESA), and manual field surveys. Three modeling scenarios were evaluated, with and without stream topology corrections, using the WaTEM/SEDEM model. It details the global data used, the methodology of the field survey, the simulation and validation of data, and the critical point identification. Significant discrepancies in long-term sediment transport predictions were found, depending on the land use data source. This study addresses watershed model validity and potential errors and recommendations for the use of globally available data.

Hydrometeorological Trends in a Low-Gradient Forested Watershed on the Southeastern Atlantic Coastal Plain in the USA

Hydrology and meteorological data from relatively undisturbed watersheds aid in identifying effects on ecosystem services, tracking hydroclimatic trends, and reducing model uncertainties. Sustainable forest, water, and infrastructure management depends on assessing the impacts of extreme events and land use change on flooding, droughts, and biogeochemical processes. For example, global climate models predict more frequent high-intensity storms and longer dry periods for the southeastern USA. We summarized 17 years (2005–2021) of hydrometeorological data recorded in the 52 km2, third-order Turkey Creek watershed at the Santee Experimental Forest (SEF), Southeastern Coastal Plain, USA. This is a non-tidal headwater system of the Charleston Harbor estuary. The study period included a wide range of weather conditions; annual precipitation (P) and potential evapotranspiration (PET) ranged from 994 mm and 1212 mm in 2007 to 2243 mm and 1063 in 2015, respectively. The annual runoff coefficient (ROC) varied from 0.09 in 2007 (with water table (WT) as deep as 2.4 m below surface) to 0.52 in 2015 (with frequently ponded WT conditions), with an average of 0.22. Although the average P (1470 mm) was 11% higher than the historic 1964–1976 average (1320 mm), no significant (α= 0.05) trend was found in the annual P (p = 0.11), ROC (p = 0.17) or runoff (p = 0.27). Runoff occurred on 76.4% of all days in the study period, exceeding 20 mm/day for 1.25% of all days, mostly due to intense storms in the summer and lower ET demand in the winter. No-flow conditions were common during most of the summer growing season. WT recharge occurred during water-surplus conditions, and storm-event base flow contributed 23–47% of the total runoff as estimated using a hydrograph separation method. Storm-event peak discharge in the Turkey Creek was dominated by shallow subsurface runoff and was correlated with 48 h precipitation totals. Estimated precipitation intensity–duration–frequency and flood frequency relationships were found to be larger than those found by NOAA for the 1893–2002 period (for durations ≥ 3 h), and by USGS regional frequencies (for ≥10-year return intervals), respectively, for the same location. We recommend an integrated analysis of these data together with available water quality data to (1) assess the impacts of rising tides on the hydroperiod and biogeochemical processes in riparian forests of the estuary headwaters, (2) validate rainfall–runoff models including watershed scale models to assess land use and climate change on hydrology and water quality, and (3) inform watershed restoration goals, strategies, and infrastructure design in coastal watersheds.

Analyzing the phosphorus flow characteristics in the largest freshwater lake (Poyang Lake) watershed of China from 1950 to 2020 through a bottom-up approach of watershed-scale phosphorus substance flow model

Understanding the historical patterns of phosphorus (P) cycling is essential for sustainable P management and eutrophication mitigation in watersheds. Currently, there is a lack of long-term watershed-scale models that analyze the flow of P substances and quantify the socioeconomic patterns of P flow. This study adopted a watershed perspective and incorporated crucial economic and social subsystems related to P production, consumption, and emissions throughout the entire life cycle. Based on this approach, a bottom-up watershed P flow analysis model was developed to quantify the P cycle for the first time in the Poyang Lake watershed from 1950 to 2020 and to explore the driving factors that influence its strength by analyzing multi-year P flow results. In general, the P cycle in the Poyang Lake watershed was no longer a naturally dominated cycle but significantly influenced by human activities during the flow dynamics between 1950 and 2015. Agricultural intensification and expansion of large-scale livestock farming continue to enhance the P flow in the study area. Fertilizer P inputs from cultivation account for approximately 60% of the total inputs to farming systems, but phosphate fertilizer utilization continues to decline. Feed P inputs have continued to increase since 2007. The expansion of large-scale farming and the demand for urbanization are the main factors leading to changes in feed P input patterns. The P utilization rate for livestock farming (PUEa) is progressively higher than international levels, with PUEa increasing from 0.64% (1950) to 9.7% (2020). Additionally, per capita food P consumption in the watershed increased from 0.67 kg to 0.80 kg between 1950 and 2020. The anthropogenic P emissions have increased from 1.67 × 104 t (1950) to 8.73 × 104 t (2020), with an average annual growth rate of 2.41%. Watershed-wide P pollution emissions have increased by more than five-fold. Population growth and agricultural development are important drivers of structural changes in P flows in the study area, and they induce changes in social conditions, including agricultural production, dietary structure, and consumption levels, further dominating the cyclic patterns of P use, discharge, and recycling. This study provides a broader and applicable P flow model to measure the characteristics of the P cycle throughout the watershed social system as well as provides methodological support and policy insights for large lakes in rapidly developing areas or countries to easily present P flow structures and sustainably manage P resources.

Watershed scale modeling of Dissolved organic carbon export from variable source areas

Dissolved organic carbon (DOC) in surface water influences the global carbon cycle, ecosystem productivity, and water quality in potable water supply systems. Few physically based watershed models can simulate carbon cycling and predict DOC in surface waters under the influence of natural and anthropogenic drivers. In this work we transform the SWAT-Carbon (C) model to simulate DOC from variable source runoff areas in a humid forested watershed in the northeastern United States. Remotely sensed data were used to parameterize and simulate forest growth and evapotranspiration. The calibrated model accurately simulated streamflow and DOC flux at six sites across the watershed compared to measured data. The DOC predictions across sites showed model sensitivity to soil properties, particularly soil depth and available water capacity. The spatial distribution of DOC export across the watershed followed the pattern of surface runoff from variable source areas. Model sensitivity of DOC flux showed greater sensitivity to changes in precipitation than temperature. The overall good performance of the model makes it a valuable tool for watershed-scale modeling of DOC to understand the influence of climate and watershed management towards developing mitigation strategies. The methods presented in this study can be used in forested watersheds in regions where runoff from variable source areas is important for water quality predictions.

Incorporating Wetland Delineation and Impacts in Watershed-Scale Hydrologic Modeling

In semi-distributed hydrologic models, it is difficult to account for the impacts of wetlands on hydrologic processes, as they are based on lumped, subbasin-scale wetland concepts. It is a challenge to incorporate the influences of individual small wetlands into watershed-scale models by using lumped parameterization. The objective of this study was to improve watershed-scale hydrologic modeling by taking into account real wetland features during the wetland parameterization. To achieve this objective, a joint modeling framework was proposed to couple a surface delineation algorithm with a semi-distributed hydrologic model and then applied to the Upper Turtle River watershed in North Dakota, USA. The delineation algorithm identified the topographic properties of wetlands, which were further utilized for wetland parameterization. A nonlinear area–storage relationship was determined and used in the estimation of the wetland-related parameters. The results demonstrated that the new joint modeling approach effectively avoided misestimating the wetland-related parameters by accounting for real topographic characteristics (e.g., storage, ponding area, and contributing area) of identified wetlands and their influences, and provided improved modeling of the hydrologic processes in such a wetland-dominated watershed.

Development and evaluation of GIS-based runoff and sediment yield watershed scale model

Development and evaluation of GIS-based runoff and sediment yield watershed scale model

The impact of overgrazing on water fluxes in a semi-arid watershed – The suitability of watershed scale modeling in a data scarce area

Study regionSouth Africa. Study focusThis study focuses on the impact of overgrazing on the water resources in a semi-arid catchment in South Africa. We have applied the SWAT+ model to a data-scarce area. During the modeling process, hydropedological principles were applied in model parameterization and analysis of simulation results to identify areas which are sensitive to overgrazing. The scenario analysis indicates that overgrazing might not necessarily have a large impact on the water balance of the whole watershed, but may have negative impacts at the local subbasin scale. These impacts are increased surface runoff and evaporation which are the consequence of compaction of topsoils. New hydrological insights for the regionThe application of hydropedological principles in the analysis of simulation results help to identify areas sensitive to overgrazing. Shallow soils, soils with low surface infiltration capacities and hydromorphic soils are vulnerable to adverse effects from overgrazing.

An integrated framework for simultaneously modeling primary and secondary salinity at a watershed scale

Salinity is a major environmental phenomenon that affects watersheds and irrigated areas worldwide. The watershed-scale salinity modeling requires a watershed-scale model like the Soil and Water Assessment Tool (SWAT) that simulates hydrologic processes throughout a watershed. The Richards equation can assist in addressing very complex processes that affect water flow in the unsaturated root zone influenced by gravity and capillarity at a field scale. The SWAT model does not use the Richards equation for modeling flows in the root zone, resulting in less accuracy in simulating hydrologic processes related to agriculture. This study presents an integrated framework for the watershed-scale salinity modeling by modifying the water-salt balance (SWAT-S) model linked to the Soil Water Atmosphere Plant (SWAP) model. The integrated framework was applied to the Mond River Basin of Iran. The model was calibrated and validated with historical records of the river discharge and salt concentration using the SUFI-2 optimization algorithm to evaluate the model's strength and to verify the accuracy of simulations. The model performance was satisfactory in calibration and validation periods with the coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE), Percent bias (|PBIAS|), and RMSE-observations standard deviation ratio (RSR) ranging from 0.56 to 0.87, 0.52 to 0.87, 0.2 to 22.2, and 0.37 to 0.69, respectively. Also, P‐factor values were more than 0.65, while R‐factor values were<1.40.

Water Quality Modeling Using Soil and Water Assessment Tool: A Case Study of Rawal Watershed

The water quality of Rawal watershed has been highly deteriorated because of increased concentration of organic nitrogen and phosphorous coming from non-point sources causing eutrophication. The main objective of this study was to use a watershed scale model SWAT (Soil &amp; Water Assessment Tool) as a modeling tool for predicting the impact of the Land Use change on water quality of Rawal Lake. Specific objectives were to (a)develop pollution source inventory mapping(b) quantify the pollutant load (organic nitrogen and phosphorus) with respect to Land Use change that causes eutrophication and (c) model the alternative Best Management Practices (BMP’s) and evaluate their effectiveness. In the pre field phase the collection and preprocessing of data (DEM &amp; Landsat images (30m resolution)) was done. Land Use (2001 &amp; 2010) classification was done using Landsat imagery in ArcGIS. For the pollution source inventory, mapping the study area was surveyed. In the post field phase the model was calibrated (2002-2006) by using the observed and simulated surface runoff data and then validated (2007-2010) .The, model’s accuracy was further verified by using R2 and Nash Sutcliffe Efficiency (NSE). SWAT simulations resulted in 392.40 % and 391.72 % increase in the quantity of organic nitrogen and phosphorus with respect to Land Use change (2001 &amp; 2010). By the application of BMP’s such as filter strips, the average reduction in the concentration of N could be 75.155% while that of P could be 96.93%, similarly by the application of terracing the average reduction in the concentration of N could be 52.73% while that of P could be 94.18% in the selected sub basins. By the application of contouring the average reduction of 35.64% for N and 92.09% for P could be achieved. This study would provide decision maker a source of information on most feasible and cost effective BMP’s.

Development of a simulation method for paddy fields based on surface FTABLE of hydrological simulation program–FORTRAN

The Hydrological Simulation Program–FORTRAN (HSPF) is a widely used watershed-scale model; however, it does not comprise any functions that can be used to simulate rice paddy fields, thereby hindering its applicability in many Asian countries. To address this limitation, a paddy field simulation method was developed by considering the water detention effect and seasonal changes in the outlet height of paddy fields; this was achieved using the existing functions of HSPF. Surface FTABLE, a function of the relationship between surface water storage and outflow, was applied to represent the physical structure and inundated condition of paddy fields. Surface FTABLE was temporally changed by Special Actions, an HSPF module, to reflect the seasonal variation in drainage outlet height. By employing these methods, HSPF was applied to paddy fields for evaluating the model performance. On comparing the simulated and observed values of ponding depth and surface outflow, the model showed good performance with a coefficient of determination that ranged from 0.71 to 0.89 and an index of agreement that ranged from 0.92 to 0.97. Comparing the results of the simulation performed with or without Surface FTABLE, the simulation with Surface FTABLE exhibited a reduced surface outflow (−40.0%) due to the blocking effect of the paddy field, a decreased infiltration (−17.3%) due to the saturation of the upper soil zone, and a higher level of soil water in all subsurface layers. Based on these differences in each component, it is necessary to apply Surface FTABLE when considering the hydrological processes of paddy fields for HSPF modeling. The simulation method developed in this study only uses the existing functions of HSPF without performing any external modifications; therefore, it can be used conveniently to improve the applicability of HSPF in rice-growing regions.

Optimizing nature-based solutions by combining social equity, hydro-environmental performance, and economic costs through a novel Gini coefficient

A robust multi-functional framework for widespread planning of nature-based solutions (NBS) must incorporate components of social equity and hydro-environmental performance in a cost-effective manner. NBS systems address stormwater mitigation by increasing on-site infiltration and evaporation through enhanced greenspace while also improving various components of societal well-being, such as physical health (e.g., heart disease, diabetes), mental health (e.g., post-traumatic stress disorder, depression), and social cohesion. However, current optimization tools for NBS systems rely on stormwater quantity abatement and, to a lesser extent, economic costs and environmental pollutant mitigation. Therefore, the objective of this study is to explore how NBS planning may be improved to maximize hydrological, environmental, and social co-benefits in an unequivocal and equitable manner. Here, a novel equity-based indexing framework is proposed to better understand how we might optimize social and physical functionalities of NBS systems as a function of transdisciplinary characteristics. Specifically, this study explores the spatial tradeoffs associated with NBS allocation by first optimizing a local watershed-scale model according to traditional metrics of stormwater efficacy (e.g., cost efficiency, hydrological runoff reduction, and pollutant load reduction) using SWMM modeling. The statistical dispersion of social health is then identified using the Area Deprivation Index (ADI), which is a high-resolution spatial account of socioeconomic disadvantages that have been linked to adverse health outcomes, according to United States census properties. As NBSs have been shown to mitigate various adverse health conditions through increased urban greening, this improved understanding of geospatial health characteristics may be leveraged to inform an explicit representation of social wellness within NBS planning frameworks. This study presents and demonstrates a novel framework for integrating hydro-environmental modeling, economic efficiency, and social health deprivation using a dimensionless Gini coefficient, which is intended to spur the positive connection of social and physical influences within robust NBS planning. Hydro-environmental risk (according to hydro-dynamic modeling) and social disparity (according to ADI distribution) are combined within a common measurement unit to capture variation across spatial domains and to optimize fair distribution across the study area. A comparison between traditional SWMM-based optimization and the proposed Gini-based framework reveals how the spatial allocation of NBSs within the watershed may be structured to address significantly more areas of social health deprivation while achieving similar hydro-environmental performance and cost-efficiency. The results of a case study for NBS planning in the White Oak Bayou watershed in Houston, Texas, USA revealed runoff volume reductions of 3.45% and 3.38%, pollutant load reductions of 11.15% and 11.28%, and ADI mitigation metrics of 16.84% and 35.32% for the SWMM-based and the Gini-based approaches, respectively, according to similar cost expenditures. As such, the proposed framework enables an analytical approach for balancing the spatial tradeoffs of overlapping human-water goals in NBS planning while maintaining hydro-environmental robustness and economic efficiency.

A Terrestrial‐Aquatic Model Reveals Cross‐Scale Interactions Regulate Lateral Dissolved Organic Carbon Transport From Terrestrial Ecosystems

AbstractLateral carbon transport (LCT), the flux of terrestrial C transported to aquatic ecosystems, displaces carbon (C) across the terrestrial‐aquatic continuum and is on the same order of magnitude as terrestrial net ecosystem production. However, few continental scale C models include LCT or the C‐hydrology linkages necessary for modeling LCT. Those that do exist, borrow processes and conceptual understanding from watershed scale models, assuming that large‐scale and small‐scale drivers of LCT are the same. We develop a conceptual framework of LCT, which focuses on lateral dissolved organic carbon (DOC) transport (LCT‐DOC), and operationalize it with a coupled terrestrial‐aquatic C and hydrology model. After comparing our model LCT‐DOC to previous estimates derived from a summation of landscape scale fluxes for the Contiguous U.S., we use model experiments to partition the importance of LCT‐DOC drivers including total annual precipitation, air temperature, and plant traits, which interact across regional and local scales. We find that climate is the strongest driver of LCT‐DOC, where LCT‐DOC is positively related to precipitation but inversely related to temperature at continental scales. However, the net effect of climate on LCT‐DOC is the product of cross‐scale interactions between climate and vegetation. Plant traits also interact strongly with climate and have a measurable influence on LCT‐DOC, with water use efficiency as the most influential plant trait because it couples terrestrial water and C cycling. We demonstrate that our conceptual framework and relatively simple linked C‐hydrology process model of LCT‐DOC can inform hypotheses and predict LCT‐DOC.

Effects of DEM Depression Filling on River Drainage Patterns and Surface Runoff Generated by 2D Rain-on-Grid Scenarios

Topographic depressions in Digital Elevation Models (DEMs) have been traditionally seen as a feature to be removed as no outward flow direction is available to route and accumulate flows. Therefore, to simplify hydrologic analysis for practical purposes, the common approach treated all depressions in DEMs as artefacts and completely removed them in DEMs’ data preprocessing prior to modelling. However, the effects of depression filling on both the geomorphic structure of the river network and surface runoff is still not clear. The use of two-dimensional (2D) hydrodynamic modeling to track inundation patterns has the potential to provide novel point of views on this issue. Specifically, there is no need to remove topographic depression from DEM, as performed in the use of traditional methods for the automatic extraction of river networks, so that their effects can be directly taken into account in simulated drainage patterns and in the associated hydrologic response. The novelty introduced in this work is the evaluation of the effects of DEM depression filling on both the structure of the net-points characterizing the simulated networks and the hydrologic response of the watersheds to simplified rainfall scenarios. The results highlight how important these effects might be in practical applications, providing new insights in the field of watershed-scale modeling.

1 to 1000 Policy: Controlling Phosphorous Pollution from Tea Farms with Bioretention Cells

When implementing nonpoint source pollution control plans, the size or number of required controlling facilities is a very practical issue. However, quantifying nonpoint source pollution is difficult because it is generated by variable and random rainfall events. This study develops a two-stage optimization process to demonstrate the determination of the optimal bioretention cell size for tea farm pollution control. The optimization process was based on a verified watershed-scale model and a verified site-scale model. The verified watershed model was used to obtain total phosphorous (TP) reduction loads. Once the goal of watershed management was decided, the reduction loads were then allocated and the unit reduction loads were determined. Using the unit reduction loads, the verified tea farm model was used to assess the optimal bioretention cell size for tea farms. A case study using the Jinggualiao stream in the Feitsui Reservoir watershed, Taipei, Taiwan was presented. The results showed that the unit tea farm TP reduction loads were 270 g/ha-year and 326 g/ha-year to reach two water quality goals, and a total of 350 m2 and 600 m2 of bioretention cells were needed, respectively. A 1 to 1000 ratio of the standard bioretention cell area to the tea farm area is recommended as a general control rule.

Watershed-scale modelling of the irrigated rice farming system at Muda, Malaysia, using the Soil Water Assessment Tool

ABSTRACT Agricultural production in a highly managed watershed is challenging to capture in models due to its complexity and large hydrological, management, and crop data requirements. We evaluated hydro-crop simulation of Malaysia’s largest rice granary using the Soil Water Assessment Tool (SWAT). The 4515 km2 watershed is characterized by dams in the upper sub-watersheds that drain towards 1007 km2 of rice paddies. Monthly averaged streamflow simulation produced Nash-Sutcliffe efficiencies and coefficients of determination between 0.84 and 0.90 in both calibration and validation periods. Meanwhile, the normalized root mean square error and the percent bias for rice yield simulation in off and main seasons of rice planting were within ± 10%. Investigation of rice yield loss processes revealed a stronger control by solar radiation on crop growth processes compared to other hydroclimatic and environmental stresses. Our findings show that SWAT can reliably simulate streamflow and rice growth; however, it may not capture all yield loss processes.

BioRT-Flux-PIHM v1.0: a biogeochemical reactive transport model at the watershed scale

Abstract. Watersheds are the fundamental Earth surface functioning units that connect the land to aquatic systems. Many watershed-scale models represent hydrological processes but not biogeochemical reactive transport processes. This has limited our capability to understand and predict solute export, water chemistry and quality, and Earth system response to changing climate and anthropogenic conditions. Here we present a recently developed BioRT-Flux-PIHM (BioRT hereafter) v1.0, a watershed-scale biogeochemical reactive transport model. The model augments the previously developed RT-Flux-PIHM that integrates land-surface interactions, surface hydrology, and abiotic geochemical reactions. It enables the simulation of (1) shallow and deep-water partitioning to represent surface runoff, shallow soil water, and deeper groundwater and of (2) biotic processes including plant uptake, soil respiration, and nutrient transformation. The reactive transport part of the code has been verified against the widely used reactive transport code CrunchTope. BioRT-Flux-PIHM v1.0 has recently been applied in multiple watersheds under diverse climate, vegetation, and geological conditions. This paper briefly introduces the governing equations and model structure with a focus on new aspects of the model. It also showcases one hydrology example that simulates shallow and deep-water interactions and two biogeochemical examples relevant to nitrate and dissolved organic carbon (DOC). These examples are illustrated in two simulation modes of complexity. One is the spatially lumped mode (i.e., two land cells connected by one river segment) that focuses on processes and average behavior of a watershed. Another is the spatially distributed mode (i.e., hundreds of cells) that includes details of topography, land cover, and soil properties. Whereas the spatially lumped mode represents averaged properties and processes and temporal variations, the spatially distributed mode can be used to understand the impacts of spatial structure and identify hot spots of biogeochemical reactions. The model can be used to mechanistically understand coupled hydrological and biogeochemical processes under gradients of climate, vegetation, geology, and land use conditions.

Simulation of rice paddy systems in SWAT: A review of previous applications and proposed SWAT+ rice paddy module

The Soil and Water Assessment Tool (SWAT) is an ecohydrological watershed-scale model which was initially developed in the early 1990s to simulate the impacts of land use, management systems, and climate on hydrology and/or water quality. First adopted in the U.S., the use of the model then spread to Europe and then later to Asia and other regions. The range of applications that SWAT has been applied to have also expanded dramatically, which influenced ongoing model development which has been virtually continuous over the past two decades. A key component of many SWAT applications in Asia is accounting for rice paddy production that is common in some subregions within the continent. However, most of these studies do not provide explicit details of how rice production was simulated in SWAT. Other research has revealed that significant problems occur when trying to represent rice paddy systems in standard versions of SWAT, due to limitations in algorithms based on the runoff curve number approach or the pothole option. In response, key modifications have been made to SWAT in recent studies that have resulted in a more accurate representation of rice paddy systems. These developments point to the need for the incorporation of an enhanced rice paddy module within SWAT to better capture rice paddy hydrological and pollutant dynamics, which would support improved use of the model in Asia and other rice production regions. Subtopics related to simulating rice production in SWAT are discussed as follows: 1) an overview of global rice production; 2) history of SWAT development; 3) typical approaches for simulating rice production; 4) problems associated with the typical approaches; 5) recent code modifications to address deficiencies in replicating rice paddy systems; 6) recommendations for developing a standard rice paddy module for future SWAT codes. Keywords: SWAT, rice paddies, potholes, hydrology, pollutants, modified SWAT models DOI: 10.25165/j.ijabe.20221501.7147 Citation: Gassman P W, Jeong J, Boulange J, Narasimhan B, Kato T, Somura H, et al. Simulation of rice paddy systems in SWAT: A review of previous applications and proposed SWAT+ rice paddy module. Int J Agric & Biol Eng, 2022; 15(1): 1–24.

Climate change impact on water quality in the integrated Mahabad Dam watershed-reservoir system

Climate change, besides global warming, is expected to intensify the hydrological cycle, which can impact watershed nutrient yields and affect water quality in the receiving water bodies. The Mahabad Dam Reservoir in northwest Iran is a eutrophic reservoir due to excessive watershed nutrient input, which could be exacerbated due to climate change. In this regard, a holistic approach was employed by linking a climate model (CanESM2), watershed-scale model (SWAT), and reservoir water quality model (CE-QUAL-W2). The triple model investigates the cumulative climate change effects on hydrological parameters, watershed yields, and the reservoir’s water quality. The SDSM model downscaled the output of the climate model under moderate (RCP4.5) and extreme (RCP8.5) scenarios for the periods of 2021–2040 and 2041–2060. The impact of future climate conditions was investigated on the watershed runoff and total phosphorus (TP) load, and consequently, water quality status in the dam’s reservoir. The results of comparing future conditions (2021–2060) with observed present values under moderate to extreme climate scenarios showed a 4–7% temperature increase and a 6–11% precipitation decrease. Moreover, the SWAT model showed a 9–16% decline in streamflow and a 12–18% decline in the watershed TP load for the same comparative period. Finally, CE-QUAL-W2 model results showed a 3–8% increase in the reservoir water temperature and a 10–16% increase in TP concentration. It indicates that climate change would intensify the thermal stratification and eutrophication level in the reservoir, especially during the year’s warm months. This finding specifies an alarming condition that demands serious preventive and corrective measures.

How Important Are Those Fracture Zones? Scale Dependent Characteristics Revealed Through Field Studies and an Integrated Hydrological Model of a Mountain Headwater Catchment

Modeling groundwater flow in bedrock can be particularly challenging due to heterogeneities associated with fracture zones. However, fracture zones can be difficult to map, particularly in forested areas where tree cover obscures land surface features. This study presents the evidence of fracture zones in a small, snowmelt-dominated mountain headwater catchment and explores the significance of these fracture zones on groundwater flow in the catchment. A newly acquired bare earth image acquired using LiDAR identifies a previously undetected linear erosion zone that passes near a deep bedrock well at low elevation in the catchment. Borehole geophysical logs indicate more intense fracturing in this well compared to two wells at higher elevation. The well also exhibited a linear flow response during a pumping test, which is interpreted to reflect the influence of a nearby vertical fracture zone. The major ion chemistry and stable isotope composition reveal a slightly different chemical composition and a more depleted isotopic signature for this well compared to other groundwaters and surface waters sampled throughout the catchment. With this evidence of fracturing at the well scale, an integrated land surface – subsurface hydrologic model is used to explore four different model structures at the catchment scale. The model is refined in steps, beginning with a single homogeneous bedrock layer, and progressively adding 1) a network of large-scale fracture zones within the bedrock, 2) a weathered bedrock zone, and 3) an updated LiDAR-derived digital elevation model, to gain insight into how increasing subsurface geological complexity and land surface topography influence model fit to observed data and the various water balance components. Ultimately, all of the models are considered plausible, with similar overall fit to observed data (snow, streamflow, pressure heads in piezometers, and groundwater levels) and water balance results. However, the models with fracture zones and a weathered zone had better fits for the low elevation well. These models contributed slightly more baseflow (~14% of streamflow) compared to models without a weathered zone (~1%). Thus, in the watershed scale model, including a weathered bedrock zone appears to more strongly influence the hydrology than only including fracture zones.