A review of alternative climate products for SWAT modelling: Sources, assessment and future directions

Staged SWAT calibration with bias-corrected precipitation product for enhancing flow data continuity in tributaries of the Mekong River

Accurate and continuous flow data are crucial for effective water management in large river basins worldwide. However, these catchments often face challenges regarding data continuity in the mainstream and their tributaries. This study proposes a methodological framework for enhancing flow data continuity that uses a staged calibration scheme of Soil and Water Assessment Tool (SWAT) modeling with an appropriate satellite precipitation product (SPP) for each watershed. This framework is successfully applied in the Mun-Chi River Basin, the largest tributary of the Lower Mekong River, over a 20-year period at 34 stations. The staged calibration involves partitioning the catchment into smaller sub-catchments, guided by the flow monitoring stations and flow discontinuity structures such as dams. The sequential calibration from upstream to downstream partitions the overall model calibration challenge into smaller problems and contributes to a more efficient and accurate calibration and validation. Alternative SPPs were considered to overcome monitoring gaps. Their bias was corrected using quantile mapping, and their performance was evaluated with flow simulations using the SWAT model. The assessment indicates that the CMORPH-CRT product, with a spatial resolution of 0.25°, demonstrates good suitability for hydrological modeling of the Mun-Chi River Basin. The proposed methodological framework provides a continuous time series of flow discharge at multiple stations within the watershed, offering valuable insights for sustainable water resource management strategies in river systems under changing climate and land use conditions, and supporting future studies on environmental issues.

Determination of ecological statuses of streams in the Ceyhan River Basin using composition and ecological characteristics of diatoms

The present study aimed to evaluate the interactions between diatoms and ecological factors in various streams and to test the suitability of diatom indices to evaluate the ecological status of 44 streams in the Ceyhan River Basin during the spring and autumn periods of 2021 and the summer of 2022. Canonical correspondence analysis indicated the significant effects of electrical conductivity (EC), dissolved oxygen, biological oxygen demand (BOD5), total phosphorus (TP), and total nitrogen (TN) on the distribution of diatom species of streams in the Ceyhan River Basin. Of the streams, Aksu and Erkenez streams were associated with high EC, BOD5, and TP and characterized by pollution-tolerant species. Pollution-sensitive species showed close integration with Aksu Spring Brook, Gözpınar Creek, Göksun Creek, and Yeşilgöz Spring Brook, which related to a high dissolved oxygen gradient. Different eco-regional diatom indices displayed different scores, representing from bad to high ecological status in the Ceyhan River basin. Among the diatom indices, Trophic Index Turkey (TIT) proved to be the more suitable metric to assess the ecological status of streams. TIT indicated deterioration of water quality in Karasu (S06), Erkenez (S07) streams, and downstream areas of the Ceyhan River and the least distributed sampling stations in the basin. Results suggested that eco-regionally developed diatom indices, like TIT, are required to more accurately assess the ecological status of streams in the Mediterranean region. The study provides a fundamental assessment of the ecological status of streams in the Ceyhan River Basin using an appropriate diatom index before the Pazarcık-centered earthquake on February 6, 2023. Findings allow someone to assess the impact of the earthquake on diatom communities and ecological factors in the region in the future studies.

Coupling SWAT and DPSIR models for groundwater management in Mediterranean catchments

Groundwater is an essential natural resource and has a significant role in human and environmental health as well as in the economy. Management of subsurface storage remains an important option to meet the combined demands of humans and ecosystems. The increasing need to find multi-purpose solutions to address water scarcity is a global challenge. Thus, the interactions leading to surface runoff and groundwater recharge have received particular attention over the last decades. Additionally, new methods are developed to incorporate the spatial-temporal variation of recharge in groundwater modeling. In this study, groundwater recharge was spatiotemporally quantified using the Soil and Water Assessment Tool (SWAT) in the Upper Volturno-Calore hydrological basin in Italy and the results were compared with other two basins in Greece (Anthemountas and Mouriki). SWAT model was applied in actual and future projections (2022-2040) using the Representative Concentration Pathway (RCP) 4.5 emissions scenario to evaluate changes in precipitation and assess the future hydrologic conditions, along with, the Driving Force-Pressure-State-Impact-Response (DPSIR) framework that was applied in all the basins as a low-cost analysis of integrated physical, social, natural, and economic factors. According to the results, no significant variations in runoff are predicted in the Upper Volturno-Calore basin for the period 2020-2040 while the potential evapotranspiration percentage varies from 50.1% to 74.3% and infiltration around 5%. The limited primary data constitutes the main pressure in all sites and exaggerates the uncertainty of future projections.

Identifying the impact of land use land cover change on streamflow and nitrate load following modeling approach: a case study in the upstream Dong Nai River basin, Vietnam

Tri An Reservoir is a vital source of water for agriculture, industry, hydropower, and public usage in Southern Vietnam. Due to human activities, water eutrophication has become a serious problem in recent decades. This study investigated for the first time the impact of land use and land cover (LULC) change on streamflow and nitrate load from the upstream Dong Nai River basin, which is the largest watershed of the reservoir. The study utilized several LULC scenarios, including LULC 2000, 2010, and 2020. The SWAT model was applied to model the watershed during the period 1997-2009. Results showed that the hydrological model performed satisfactorily based on the Nash-Sutcliffe efficiency (NSE) coefficient, the root mean square error observations standard deviation ratio (RSR), and the percent bias (PBIAS). The average simulated values of monthly streamflow and nitrate load were 453.7, 450.0, 446.7 m³/s and 17,699.43, 17,869.13, 17,590.81 tonnes for the LULC 2000, 2010, and 2020 scenarios, respectively. There were no significant differences in streamflow and nitrate load at the basin level under the different LULC scenarios. However, when looking at the subbasin level, there were differences in nitrate load among the scenarios. This suggests that the impacts of LULC on nitrate load may be more pronounced at smaller scales. Overall, our finding underscores the importance of modeling techniques in predicting the impacts of LULC change on streamflow and water quality, which can ultimately aid in the sustainable management of water resources.

Detecting characteristics of extreme precipitation events using regional and satellite-based precipitation gridded datasets over a region in Central Europe

Perception of the spatio-temporal events of extreme precipitation and their variations is essential for diminishing the natural hazards linked with extreme events. In this research, a satellite-based precipitation dataset derived from remotely sensed soil moisture (SM2RAIN-ASCAT, obtained from ASCAT satellite soil moisture data through the Soil Moisture to Rain algorithm) was selected to evaluate the accuracy of daily precipitation and extreme events estimations against a regional gridded weather dataset by employing various performance indicators, and ETCCDI indicators (CDD, and CWD, SDII, R10mm, R20mm, R95p, R99p, Rx1day, and Rx5day). The study area includes entire Poland as well as small parts of Ukraine, Belarus, Slovakia, the Czech Republic, Russia, and Germany. According to PBIAS (~ -3.9 %) and coefficient of correlation (~0.74), SM2RAIN-ASCAT has good accuracy in the study area. Assessments reveal that, in general, over southern, mountainous part SM2RAIN-ASCAT does not have accurate estimations. According to the reference dataset, during the 2007-2019 period, on average, the length of dry days was ~22 days, while SM2RAIN-ASCAT shows ~19.6 consecutive dry days. In contrast, SM2RAIN-ASCAT overestimated (16 days/year) the consecutive wet days compared to the reference dataset (~8.7 days/year). SM2RAIN-ASCAT underestimated the number of heavy precipitation days index (R10mm) over the northern part of the region, close to the Baltic Sea), but the accuracy increased in the southern parts. SM2RAIN-ASCAT underestimated the maximum 1-day rainfall total and relative max 5-day precipitation amount indices. The total precipitation divided by the amount of wet days index shows that SM2RAIN-ASCAT has relatively acceptable accuracy in the center and south of the study area. Our results show that SM2RAIN-ASCAT should be improved for relatively higher extreme indicators.

A method for detecting the non-stationarity during high flows under global change

The sustainability of existing water resources is influenced by extreme streamflow, and climate variability and human activities are generally the major factors controlling these dynamics. However, most of previously proposed methods to determine the effects of these factors have only been developed under the assumption of stationarity. Therefore, to overcome the existing research gap, an innovative method was proposed in this study to analyze and distinguish the effects of climate variability and human activities on extreme streamflow based on the non-stationarity theory. Accordingly, a rainfall-runoff model was developed using long-term hydrological data in the watersheds of Southeast China, which cover >75,000 km². The model proposed in this study showed an acceptable performance, as indicated by the Nash-Sutcliffe efficiency coefficient (NSE), the Kling-Gupta efficiency (KGE), and percent bias (PBIAS). The NSE, KGE, and |PBIAS| were 0.67-0.75, 0.57-0.74, and 1.22-16.79 during the calibration periods, respectively. And the NSE, KGE, and |PBIAS| were 0.69-0.77, 0.65-0.76, and 0.98-17.51 during the calibration periods, respectively. The trends of the extreme streamflow were analyzed for these watersheds at different time scales. The streamflow extremes at short time scales were found to be more sensitive to changing environment than those at longer time scales. The major factor controlling streamflow extremes at short time scales was human activities and climate change may be the dominant factor influencing streamflow extremes at long time scales. The findings of this study could provide useful insights into water management under global change conditions.

Predicting phosphorus and nitrate loads by using SWAT model in Vamanapuram River Basin, Kerala, India

Evaluations of probable environmental impacts of point and diffuse source pollution at regional sizes are essential to achieve sustainable development of natural resources such as land and water. This research focused on how nitrate and phosphorus load varied over time and space in the Vamanapuram River Basin (VRB). Phosphorus and nitrate loads have been evaluated in the VRB using the semi-distributed Soil and Water Assessment Tool (SWAT) hydrological model. SWAT Calibration and Uncertainty Programs (SWAT-CUP) have simulated the developed model using the Sequential Uncertainty Fitting, version 2(SUFI-2). The developed model was simulated for 2001 to 2008, and it was split into two-phase calibration and validation phases. Model performance was evaluated by the percentage of bias (PBAIS) and Nash-Sutcliffe efficiency coefficient (NSE). The simulated performance of nitrate was indicated as NSE = 0.22-0.59 and PBIAS = 51.86-65.88. The simulated performance of phosphorus showed NSE = 0.06-0.33 and PBIAS = 15.14-33.97. Total Phosphorus load was most sensitive to the organic Phosphorus enrichment ratio (ERORGP) and CH_N2 for streamflow simulation. This study concluded that the South-western region was a high potential for nutrient loads. This study will explain the nutrient load and guidelines for land management practice in the study area.

The recent Asian elephant range expansion in Yunnan, China, is associated with climate change and enforced protection efforts in human-dominated landscapes

Recently, the northward movement of Asian elephants (Elephas maximus) in Yunnan, China, has attracted international attention. Climate change or human disturbances have been proposed to be the key drivers, but these hypotheses have not been rigorously tested. In this study, we quantified the relationship between climate change and human impacts on the recent range expansion of Asian elephants in southwest China. We found that the first observation probability of this species in a new place during 1959–2021 had a significant and positive association with change in air temperature and human density, resulting in a movement toward a high-latitude region with a warmer climate and higher human density; however, its association with precipitation was scale-dependent in time: positive or negative during the past 10 or 5 years, respectively. Under the enforced protection policy, human-dominated areas became preferred habitats for elephants. Our results indicate that climate change and enforced protection efforts in human-dominated landscapes in the last few decades are significant drivers of the recent range expansion of Asian elephants in Yunnan, China. It is necessary to expand the current protected areas or habitat corridors toward the north or set up new reserves in the north and set up barriers between human settlements and elephant habitats to facilitate elephant movements and minimize human-elephant conflicts under accelerated global change.

Model-based water accounting for integrated assessment of water resources systems at the basin scale

Agricultural activities in the concept of integrated water resources management play a vital role. Especially in dry and semi-dry regions, agricultural activities have the largest share of water consumption. By employing a model-based approach using modified Soil and Water Assessment Tool (SWAT agro-hydrological model), this study has prepared Water Accounting Plus (WA+) framework requirements to investigate different conditions of supply and demand in wet (1985-2000) and dry (2001-2015) periods in a semi-dry basin (Karkheh River Basin) in Iran. Our assessments based on WA+ show decreasing 10% (21.65 to 19.29 Billion Cubic Meters (BCM)/year) of precipitation in the dry period caused a 4% (0.13 BCM/year) decline in natural evapotranspiration. However, the basin experienced a 24% increment in evapotranspiration from agricultural activities at the same period, and runoff was approximately halved (2.45 BCM/year). Therefore, especially in downstream parts, surface water withdrawal has decreased by 18%. These new conditions have put pressure on groundwater resources. The aquifer extraction and total withdrawal for irrigation have grown by about 17% and 4%, respectively. Finally, it is evident that the manageable water has diminished due to climate change; not only the managed water consumption in the basin has not reduced, but it has also highly risen. The current study results help water authorities arrange new hydrological and climatic conditions strategies.

Rapid Extreme Tropical Precipitation and Flood Inundation Mapping Framework (RETRACE): Initial Testing for the 2021–2022 Malaysia Flood

The 2021–2022 flood is one of the most serious flood events in Malaysian history, with approximately 70,000 victims evacuated daily, 54 killed and total losses up to MYR 6.1 billion. From this devastating event, we realized the lack of extreme precipitation and flood inundation information, which is a common problem in tropical regions. Therefore, we developed a Rapid Extreme TRopicAl preCipitation and flood inundation mapping framEwork (RETRACE) by utilizing: (1) a cloud computing platform, the Google Earth Engine (GEE); (2) open-source satellite images from missions such as Global Precipitation Measurement (GPM), Sentinel-1 SAR and Sentinel-2 optical satellites; and (3) flood victim information. The framework was demonstrated with the 2021–2022 Malaysia flood. The preliminary results were satisfactory with an optimal threshold of five for flood inundation mapping using the Sentinel-1 SAR data, as the accuracy of inundated floods was up to 70%. Extreme daily precipitation of up to 230 mm/day was observed and resulted in an inundated area of 77.43 km2 in Peninsular Malaysia. This framework can act as a useful tool for local authorities and scientists to retrace the extreme precipitation and flood information in a relatively short period for flood management and mitigation strategy development.

Hydrological Modeling in the Chaohu Lake Basin of China—Driven by Open-Access Gridded Meteorological and Remote Sensing Precipitation Products

This study assessed the performance of two well-known gridded meteorological datasets, CFSR (Climate Forecast System Reanalysis) and CMADS (China Meteorological Assimilation Driving Datasets), and three satellite-based precipitation datasets, TRMM (Tropical Rainfall Measuring Mission), CMORPH (Climate Prediction Center morphing technique), and CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), in driving the SWAT (Soil and Water Assessment Tool) model for streamflow simulation in the Fengle watershed in the middle–lower Yangtze Plain, China. Eighteen model scenarios were generated by forcing the SWAT model with different combinations of three meteorological datasets and six precipitation datasets. Our results showed that (1) the three satellite-based precipitation datasets (i.e., TRMM, CMORPH, and CHIRPS) generally provided more accurate precipitation estimates than CFSR and CMADS. CFSR and CMADS agreed fairly well with the gauged measurements in maximum temperature, minimum temperature, and relative humidity, but large discrepancies existed for the solar radiation and wind speed. (2) The impact of precipitation data on simulated streamflow was much larger than that of other meteorological variables. Satisfactory simulations were achieved using the CMORPH precipitation data for daily streamflow simulation and the TRMM and CHIRPS precipitation data for monthly streamflow simulation. This suggests that different precipitation datasets can be used for optimal simulations at different temporal scales.

Impact Assessment of Gridded Precipitation Products on Streamflow Simulations over a Poorly Gauged Basin in El Salvador

In this study, five open access gridded precipitation (GP) products (CFSR, MSWEPv1.1, PERSIANN-CDR, CMORPH, and CHIRPSv2.0) and local climate data were evaluated over the Grande de San Miguel (GSM) River Basin in El Salvador. The main purpose was to identify optional data sources of precipitation for hydrological modelling given that ground-based precipitation gauges in El Salvador are scarce and their data includes important temporal and spatial gaps. Firstly, a direct comparison was made between the precipitation data from the five GP products and from the rain gauges. Secondly, the SWAT model was used to simulate the streamflow regimen based on the precipitation datasets. The analysis of results showed that the models produced correct predictions, and the accuracy increased as models were calibrated to each specific precipitation product. Overall, PERSIANN-CDR produced the best simulation results, including streamflow predictions in the GSM basin, and outperformed other GP products and also the results obtained from data precipitation gauges. The findings of this research support the hydrological modelling based on open-access GP products, particularly when the data from precipitation gauges are scarce and poor.

Evaluating the Potential of GloFAS-ERA5 River Discharge Reanalysis Data for Calibrating the SWAT Model in the Grande San Miguel River Basin (El Salvador)

Hydrological modelling requires accurate climate data with high spatial-temporal resolution, which is often unavailable in certain parts of the world—such as Central America. Numerous studies have previously demonstrated that in hydrological modelling, global weather reanalysis data provides a viable alternative to observed data. However, calibrating and validating models requires the use of observed discharge data, which is also frequently unavailable. Recent, global-scale applications have been developed based on weather data from reanalysis; these applications allow streamflows with satisfactory resolution to be obtained. An example is the Global Flood Awareness System (GloFAS), which uses the fifth generation of reanalysis data produced by the European Centre for Medium-Range Weather Forecasts (ERA5) as input. It provides discharge data from 1979 to the present with a resolution of 0.1°. This study assesses the potential of GloFAS for calibrating hydrological models in ungauged basins. For this purpose, the quality of data from ERA5 and from the Climate Hazards Group InfraRed Precipitation and Temperature with Station as well as the Climate Forecast System Reanalysis (CFSR) was analysed. The focus was on flow simulation using the Soil and Water Assessment Tool (SWAT) model. The models were calibrated using GloFAS discharge data. Our results indicate that all the reanalysis datasets displayed an acceptable fit with the observed precipitation and temperature data. The correlation coefficient (CC) between the reanalysis data and the observed data indicates a strong relationship at the monthly level all of the analysed stations (CC > 0.80). The Kling–Gupta Efficiency (KGE) also showed the acceptable performance of the calibrated SWAT models (KGE > 0.74). We concluded that GloFAS data has substantial potential for calibrating hydrological models that estimate the monthly streamflow in ungauged watersheds. This approach can aid water resource management.