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Raghavan Srinivasan
Departments of Ecology and Conservation Biology and Biological and Agricultural Engineering, Texas A&M University, Collage Station, TX 77843-2258, USA

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Journal article
Published: 17 August 2021 in Water
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The quantitative prediction of hydrological components through hydrological models could serve as a basis for developing better land and water management policies. This study provides a comprehensive step by step modelling approach for a small agricultural watershed using the SWAT model. The watershed is situated in Petzenkirchen in the western part of Lower Austria and has total area of 66 hectares. At present, 87% of the catchment area is arable land, 5% is used as pasture, 6% is forested and 2% is paved. The calibration approach involves a sequential calibration of the model starting from surface runoff, and groundwater flow, followed by crop yields and then soil moisture, and finally total streamflow and sediment yields. Calibration and validation are carried out using the r-package SWATplusR. The impact of each calibration step on sediment yields and total streamflow is evaluated. The results of this approach are compared with those of the conventional model calibration approach, where all the parameters governing various hydrological processes are calibrated simultaneously. Results showed that the model was capable of successfully predicting surface runoff, groundwater flow, soil profile water content, total streamflow and sediment yields with Nash-Sutcliffe efficiency (NSE) of greater than 0.75. Crop yields were also well simulated with a percent bias (PBIAS) ranging from −17% to 14%. Surface runoff calibration had the highest impact on streamflow output, improving NSE from 0.39 to 0.77. The step-wise calibration approach performed better for streamflow prediction than the simultaneous calibration approach. The results of this study show that the step-wise calibration approach is more accurate, and provides a better representation of different hydrological components and processes than the simultaneous calibration approach.

ACS Style

Francis Kilundu Musyoka; Peter Strauss; Guangju Zhao; Raghavan Srinivasan; Andreas Klik. Multi-Step Calibration Approach for SWAT Model Using Soil Moisture and Crop Yields in a Small Agricultural Catchment. Water 2021, 13, 2238 .

AMA Style

Francis Kilundu Musyoka, Peter Strauss, Guangju Zhao, Raghavan Srinivasan, Andreas Klik. Multi-Step Calibration Approach for SWAT Model Using Soil Moisture and Crop Yields in a Small Agricultural Catchment. Water. 2021; 13 (16):2238.

Chicago/Turabian Style

Francis Kilundu Musyoka; Peter Strauss; Guangju Zhao; Raghavan Srinivasan; Andreas Klik. 2021. "Multi-Step Calibration Approach for SWAT Model Using Soil Moisture and Crop Yields in a Small Agricultural Catchment." Water 13, no. 16: 2238.

Journal article
Published: 01 July 2021 in Forest Ecology and Management
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Eucalyptus tree stocking can be adjusted to increase, depending on purpose, cellulose, timber or bioenergy production, but the effect of stocking on ecosystem water balance is still understudied. Studies on soil and catchment hydrology and forest management, encompassing distinct climatic years, are needed for understudied ecosystems to improve water use efficiency and streamflow regulation, and thus bridging forestry and ecosystem processes. For different Eucalyptus dunnii stockings, we measured rainfall dynamics to quantify rainfall partitioning, soil water balance, and eucalyptus water use efficiency in a sandy soil. Total rainfall, throughfall, stemflow, canopy interception, evapotranspiration, tree growth, and water use efficiency were evaluated over a 1-year study period (5th to 6th years after planting), in low (LS: 816 trees ha−1), medium (M: 1,633 trees ha−1), medium–high (MH: 3,265 trees ha−1), and high tree stockings (HS: 6,568 trees ha−1). Tree stocking had no clear relation with the partitioning of annual rainfall (P, 2583 mm) into canopy interception (34–37% of P) and effective rainfall (63–66% of P). By increasing tree stocking from 816 to 6,568 trees ha−1, throughfall decreased from 62 to 53% of P, and stemflow increased from 2.1 to 12.7% of P. Estimated deep drainage was <0.16% of P, even though the annual rainfall was almost double of historical rainfall and surface runoff was only 5.7% of P. Thus, groundwater recharge in Eucalyptus plantation may be potentially low even with high rainfall in a soil with high infiltration and low slope (about 4%). Cumulative evapotranspiration varied between 1304 and 1438 mm (50–56% of P), highest for high tree stocking, whereas daily evapotranspiration rates varied between 0.8- and 11.7-mm d−1. From the 5th to the 6th year after planting, the individual wood production varied from 4.9 (HS) to 51.8 kg−1 tree (LS), and stand wood production varied from 27.1 (MHS) to 42.2 (LS) Mg ha−1 yr−1. Water use efficiency varied from 2.1 to 3.1 g L−1, respectively for MHS and LS. Industrial eucalyptus planted in sandy soils at high stocking for energy production may overuse stored water, affecting long-term forest sustainability. Therefore, the challenge is decreasing evaporation from soil and canopy and increasing green-water use efficiency, while generating surface runoff for ecological flows and groundwater recharge (blue water flow).

ACS Style

José Miguel Reichert; Juliana Prevedello; Paulo Ivonir Gubiani; Eduardo Saldanha Vogelmann; Dalvan José Reinert; Claudine Ohana Barcellos Consensa; Júlio Cesar Wincher Soares; Raghavan Srinivasan. Eucalyptus tree stockings effect on water balance and use efficiency in subtropical sandy soil. Forest Ecology and Management 2021, 497, 119473 .

AMA Style

José Miguel Reichert, Juliana Prevedello, Paulo Ivonir Gubiani, Eduardo Saldanha Vogelmann, Dalvan José Reinert, Claudine Ohana Barcellos Consensa, Júlio Cesar Wincher Soares, Raghavan Srinivasan. Eucalyptus tree stockings effect on water balance and use efficiency in subtropical sandy soil. Forest Ecology and Management. 2021; 497 ():119473.

Chicago/Turabian Style

José Miguel Reichert; Juliana Prevedello; Paulo Ivonir Gubiani; Eduardo Saldanha Vogelmann; Dalvan José Reinert; Claudine Ohana Barcellos Consensa; Júlio Cesar Wincher Soares; Raghavan Srinivasan. 2021. "Eucalyptus tree stockings effect on water balance and use efficiency in subtropical sandy soil." Forest Ecology and Management 497, no. : 119473.

Original paper
Published: 05 May 2021 in Theoretical and Applied Climatology
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This work evaluated the simulation of streamflow using observed and estimated gridded meteorological datasets and the Soil and Water Assessment Tool (SWAT) model for a humid area with scarce data in northeastern Brazil. The coefficient of determination (R2), Nash-Sutcliffe efficiency (NS), root mean square error (RMSE), normalized root mean square error (NRMSE), and percent bias (PBIAS) were used to assess the SWAT results yielded by estimated and observed rainfall data. The hydrological modeling data from three streamflow stations were used (2000 to 2006 for calibration and 2007 to 2010 for validation). The results show that at daily scale, the estimated rainfall data show a poor agreement (R2 ranging from 0.22 to 0.04) with the observed rainfall but good agreement at monthly (R2 = 0.85) and annual scales (R2 = 0.80). The results showed that estimated accumulated precipitation overestimated the observed data. The results showed that R2 ranged from 0.51 to 0.55 at monthly scale and 0.44-0.52 at annual scale. However, the global data can represent well the variability of rainfall within the region. The results indicated a good correlation in the seasonal variability (R2 ranged from 0.72 to 0.60). The modeling results using monthly TRMM data and observed rainfall data showed good values of NS and R2 during calibration and validation, but PBIAS was unsatisfactory for the three streamflow gauges. The streamflow estimates from the SWAT model using data from the TRMM satellite showed that such data are capable of generating satisfactory results after calibration, although measured rainfall data presented better results; the data could support areas with scarce rainfall data and be applied to other river basins, for example, to analyze the hydrological potential of other basins in the coastal region of northeastern Brazil. Over the past three decades, considerable advances have been made in remote sensing with environmental satellites, increasing the amount of information available, including rainfall estimates. In this context, the use of TRMM data to estimate rainfall has ultimately been shown to be an interesting alternative for areas with scarce rainfall data.

ACS Style

Jussara Freire De Souza Viana; Suzana Maria Gico Lima Montenegro; Bernardo Barbosa da Silva; Richarde Marques da Silva; Raghavan Srinivasan; Celso Augusto Guimarães Santos; Diego Cezar Dos Santos Araujo; Clara Gadelha Tavares. Evaluation of gridded meteorological datasets and their potential hydrological application to a humid area with scarce data for Pirapama River basin, northeastern Brazil. Theoretical and Applied Climatology 2021, 145, 393 -410.

AMA Style

Jussara Freire De Souza Viana, Suzana Maria Gico Lima Montenegro, Bernardo Barbosa da Silva, Richarde Marques da Silva, Raghavan Srinivasan, Celso Augusto Guimarães Santos, Diego Cezar Dos Santos Araujo, Clara Gadelha Tavares. Evaluation of gridded meteorological datasets and their potential hydrological application to a humid area with scarce data for Pirapama River basin, northeastern Brazil. Theoretical and Applied Climatology. 2021; 145 (1-2):393-410.

Chicago/Turabian Style

Jussara Freire De Souza Viana; Suzana Maria Gico Lima Montenegro; Bernardo Barbosa da Silva; Richarde Marques da Silva; Raghavan Srinivasan; Celso Augusto Guimarães Santos; Diego Cezar Dos Santos Araujo; Clara Gadelha Tavares. 2021. "Evaluation of gridded meteorological datasets and their potential hydrological application to a humid area with scarce data for Pirapama River basin, northeastern Brazil." Theoretical and Applied Climatology 145, no. 1-2: 393-410.

Preprint content
Published: 28 April 2021
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Environmental models often require soil maps to represent the spatial variability of soil attributes. However, mapping soils using conventional in-situ survey protocols is time-consuming and costly. As an alternative, digital soil mapping offers a fast-mapping approach that might be used to monitor soil attributes and their interrelationships over large areas. In Brazil, conventional survey methods are still widely used, and thus maps still in development are considered as the state-of-the-art products for decades. In this study, we address this lack of updated spatial information on many soil attributes by producing regional statistical soil models using an innovative framework. This new framework attempts to reduce prediction redundancies due to high multicollinearity, by implementing a Feature Selector algorithm. This is expected to improve a model’s strength by decreasing its unexplained variance. The framework’s core is composed of the Soil-Landscape Estimation and Evaluation Program (SLEEP) and a calibrated Gradient Boosting Model capable of modelling the spatial distribution of soil attributes at multiple soil depths. These models allowed us to explain the spatial distribution of some basic soil attributes (physical and chemical), and its environmental drivers. The model training and testing approach used 30 environmental attributes, and data from 223 soil profiles for the state of Pernambuco, Brazil. Our models demonstrated a consistent potential to perform spatial extrapolations with r2 ranging from 0.8 to 0.97, and PBIAS from -0.51 to 2.03. The properties related to topographic and climatic conditions were dominating when estimating the number of horizons, percentage of silt and the sum of bases (a measure of soil fertility). We believe that our framework features high flexibility, while reducing capital investments when compared to in situ surveys and traditional mapping protocols. These findings also have implications for the improvement and testing of pedotransfer functions. We thank FACEPE for funding this through APQ 0646-9.25/16.

ACS Style

Rodrigo Miranda; Rodolfo Nobrega; Estevão Silva; Jadson Freire; José Filho; Magna Moura; Alexandre Barros; Alzira Saraiva; Anne Verhoef; Raghavan Srinivasan; Suzana Montenegro; Maria Araújo; Josiclêda Galvíncio. Digital soil mapping using machine learning techniques in a varied tropical environment. 2021, 1 .

AMA Style

Rodrigo Miranda, Rodolfo Nobrega, Estevão Silva, Jadson Freire, José Filho, Magna Moura, Alexandre Barros, Alzira Saraiva, Anne Verhoef, Raghavan Srinivasan, Suzana Montenegro, Maria Araújo, Josiclêda Galvíncio. Digital soil mapping using machine learning techniques in a varied tropical environment. . 2021; ():1.

Chicago/Turabian Style

Rodrigo Miranda; Rodolfo Nobrega; Estevão Silva; Jadson Freire; José Filho; Magna Moura; Alexandre Barros; Alzira Saraiva; Anne Verhoef; Raghavan Srinivasan; Suzana Montenegro; Maria Araújo; Josiclêda Galvíncio. 2021. "Digital soil mapping using machine learning techniques in a varied tropical environment." , no. : 1.

Research article
Published: 31 March 2021 in Hydrological Sciences Journal
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In small catchments, the time interval most commonly used for simulation, daily or monthly, may not be sufficient to accurately capture the time distribution of hydrological processes. In this paper, the Soil and Water Assessment Tool (SWAT) was used to perform an hourly long-term streamflow and sediment load simulation in the small (4.8 km2) and forested Aixola catchment (northern Spain). From this simulation 10 runoff events were tested; the most satisfactory results for streamflow were obtained under wet antecedent conditions. However, simulated sediment load was underestimated during the peaks and remained high towards the end of the event. Furthermore, the influence of the precipitation time-step (1–4 h, daily) was not relevant in the streamflow simulation but has influence on sediment simulation. The best results obtained accumulating at the daily step simulations obtained at hourly time-step. This paper shows that sub-daily modelling improves water and especially sediment yield results, however, improvements are still needed in timing related routines.

ACS Style

Maite Meaurio; Ane Zabaleta; Raghavan Srinivasan; Sabine Sauvage; José-Miguel Sánchez-Pérez; Juan Luis Lechuga-Crespo; Iñaki Antiguedad. Long-term and event-scale sub-daily streamflow and sediment simulation in a small forested catchment. Hydrological Sciences Journal 2021, 66, 862 -873.

AMA Style

Maite Meaurio, Ane Zabaleta, Raghavan Srinivasan, Sabine Sauvage, José-Miguel Sánchez-Pérez, Juan Luis Lechuga-Crespo, Iñaki Antiguedad. Long-term and event-scale sub-daily streamflow and sediment simulation in a small forested catchment. Hydrological Sciences Journal. 2021; 66 (5):862-873.

Chicago/Turabian Style

Maite Meaurio; Ane Zabaleta; Raghavan Srinivasan; Sabine Sauvage; José-Miguel Sánchez-Pérez; Juan Luis Lechuga-Crespo; Iñaki Antiguedad. 2021. "Long-term and event-scale sub-daily streamflow and sediment simulation in a small forested catchment." Hydrological Sciences Journal 66, no. 5: 862-873.

Journal article
Published: 05 February 2021 in Water
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The quality of input data and the process of watershed delineation can affect the accuracy of runoff predictions in watershed modeling. The Upper Mississippi River Basin was selected to evaluate the effects of subbasin and/or hydrologic response unit (HRU) delineations and the density of climate dataset on the simulated streamflow and water balance components using the Hydrologic and Water Quality System (HAWQS) platform. Five scenarios were examined with the same parameter set, including 8- and 12-digit hydrologic unit codes, two levels of HRU thresholds and two climate data densities. Results showed that statistic evaluations of monthly streamflow from 1983 to 2005 were satisfactory at some gauge sites but were relatively worse at others when shifting from 8-digit to 12-digit subbasins, revealing that the hydrologic response to delineation schemes can vary across a large basin. Average channel slope and drainage density increased significantly from 8-digit to 12-digit subbasins. This resulted in higher lateral flow and groundwater flow estimates, especially for the lateral flow. Moreover, a finer HRU delineation tends to generate more runoff because it captures a refined level of watershed spatial variability. The analysis of climate datasets revealed that denser climate data produced higher predicted runoff, especially for summer months.

ACS Style

Manyu Chen; Yuanlai Cui; Philip Gassman; Raghavan Srinivasan. Effect of Watershed Delineation and Climate Datasets Density on Runoff Predictions for the Upper Mississippi River Basin Using SWAT within HAWQS. Water 2021, 13, 422 .

AMA Style

Manyu Chen, Yuanlai Cui, Philip Gassman, Raghavan Srinivasan. Effect of Watershed Delineation and Climate Datasets Density on Runoff Predictions for the Upper Mississippi River Basin Using SWAT within HAWQS. Water. 2021; 13 (4):422.

Chicago/Turabian Style

Manyu Chen; Yuanlai Cui; Philip Gassman; Raghavan Srinivasan. 2021. "Effect of Watershed Delineation and Climate Datasets Density on Runoff Predictions for the Upper Mississippi River Basin Using SWAT within HAWQS." Water 13, no. 4: 422.

Journal article
Published: 18 December 2020 in Sustainability
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In the face of future climate change, Europe has encouraged the adoption of biofuel crops by its farmers. Such land-use changes can have significant impacts on the water balance and hydrological behavior of a system. While the heavy pesticide use associated with biofuel crops has been extensively studied, the water balance impacts of these crops have been far less studied. We conducted scenario analyses using the Soil and Water Assessment Tool (SWAT) to determine the effects of farm-scale biofuel crop adoption (rapeseed) on a basin’s water balance. We found that rapeseed adoption does not support the goal of developing a sustainable agricultural landscape in the Czech Republic. The adoption of rapeseed also had disproportionate effects on a basin’s water balance depending on its location in the basin. Additionally, discharge (especially surface runoff ratios), evapotranspiration, and available soil water content display significant shifts in the rapeseed adoption scenarios.

ACS Style

Nina Noreika; Tailin Li; David Zumr; Josef Krasa; Tomas Dostal; Raghavan Srinivasan. Farm-Scale Biofuel Crop Adoption and Its Effects on In-Basin Water Balance. Sustainability 2020, 12, 10596 .

AMA Style

Nina Noreika, Tailin Li, David Zumr, Josef Krasa, Tomas Dostal, Raghavan Srinivasan. Farm-Scale Biofuel Crop Adoption and Its Effects on In-Basin Water Balance. Sustainability. 2020; 12 (24):10596.

Chicago/Turabian Style

Nina Noreika; Tailin Li; David Zumr; Josef Krasa; Tomas Dostal; Raghavan Srinivasan. 2020. "Farm-Scale Biofuel Crop Adoption and Its Effects on In-Basin Water Balance." Sustainability 12, no. 24: 10596.

Journal article
Published: 01 November 2020 in International Soil and Water Conservation Research
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Ecological and hydrological impacts are expected when watersheds are under commercial eucalyptus. In this study we evaluated event-based hydrology and sedimentation in paired watersheds under commercial eucalyptus and grasslands cover. Flow, suspended sediment concentration, and sediment production were measured and simulated with the Limburg Soil Erosion Model (LISEM) in paired hydrographic watersheds located in southern Brazil; one occupied with 7-years old Eucalyptus saligna plantation (forest watershed-FW; 0.83 km2) and another Pampa biome with native and exotic grasses used for beef cattle production (grassland watershed-GW; 1.10 km2). The effect of rainfall on hydrological and sedimentological variables was more evident in GW compared with FW. The shape of the hydrograph was steepest in GW, with rapid, marked increase and decrease in flow during rainfall. The parameters changed for model calibration in FW and GW were soil saturated hydraulic conductivity, initial soil moisture, and Manning roughness coefficient, whereby the statistical performance was classified as good (NSE> 0.75). Fourteen events different from those used in the calibration process were validated for FW and GW, with NSE index classified as “good” and “very good” for hydrology. Our study shows limitations of LISEM in calibrating and validating the sediment yield for individual events due to the spatial variability of factors controlling soil erosion. The validated modeling results of this study may be applied in simulating soil and crop scenarios in watersheds cultivated with commercial forest and grassland for grazing.

ACS Style

Éderson Diniz Ebling; José Miguel Reichert; Jhon Jairo Zuluaga Peláez; Miriam Fernanda Rodrigues; Mirian Lago Valente; Rosane Barbosa Lopes Cavalcante; Paolo Reggiani; Raghavan Srinivasan. Event-based hydrology and sedimentation in paired watersheds under commercial eucalyptus and grasslands in the Brazilian Pampa biome. International Soil and Water Conservation Research 2020, 9, 180 -194.

AMA Style

Éderson Diniz Ebling, José Miguel Reichert, Jhon Jairo Zuluaga Peláez, Miriam Fernanda Rodrigues, Mirian Lago Valente, Rosane Barbosa Lopes Cavalcante, Paolo Reggiani, Raghavan Srinivasan. Event-based hydrology and sedimentation in paired watersheds under commercial eucalyptus and grasslands in the Brazilian Pampa biome. International Soil and Water Conservation Research. 2020; 9 (2):180-194.

Chicago/Turabian Style

Éderson Diniz Ebling; José Miguel Reichert; Jhon Jairo Zuluaga Peláez; Miriam Fernanda Rodrigues; Mirian Lago Valente; Rosane Barbosa Lopes Cavalcante; Paolo Reggiani; Raghavan Srinivasan. 2020. "Event-based hydrology and sedimentation in paired watersheds under commercial eucalyptus and grasslands in the Brazilian Pampa biome." International Soil and Water Conservation Research 9, no. 2: 180-194.

Journal article
Published: 21 September 2020 in Remote Sensing
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The spatial and temporal scale of rainfall datasets is crucial in modeling hydrological processes. Recently, open-access satellite precipitation products with improved resolution have evolved as a potential alternative to sparsely distributed ground-based observations, which sometimes fail to capture the spatial variability of rainfall. However, the reliability and accuracy of the satellite precipitation products in simulating streamflow need to be verified. In this context, the objective of the current study is to assess the performance of three rainfall datasets in the prediction of daily and monthly streamflow using Soil and Water Assessment Tool (SWAT). We used rainfall data from three different sources: Climate Hazards Group InfraRed Rainfall with Station data (CHIRPS), Climate Forecast System Reanalysis (CFSR) and observed rain gauge data. Daily and monthly rainfall measurements from CHIRPS and CFSR were validated using widely accepted statistical measures, namely, correlation coefficient (CC), root mean squared error (RMSE), probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI). The results showed that CHIRPS was in better agreement with ground-based rainfall at daily and monthly scale, with high rainfall detection ability, in comparison with the CFSR product. Streamflow prediction across multiple watersheds was also evaluated using Kling-Gupta Efficiency (KGE), Nash-Sutcliffe Efficiency (NSE) and Percent BIAS (PBIAS). Irrespective of the climatic characteristics, the hydrologic simulations of CHIRPS showed better agreement with the observed at the monthly scale with the majority of the NSE values ranging between 0.40 and 0.78, and KGE values ranging between 0.62 and 0.82. Overall, CHIRPS outperformed the CFSR rainfall product in driving SWAT for streamflow simulations across the multiple watersheds selected for the study. The results from the current study demonstrate the potential of CHIRPS as an alternate open access rainfall input to the hydrologic model.

ACS Style

Yeganantham Dhanesh; V. Bindhu; Javier Senent-Aparicio; Tássia Brighenti; Essayas Ayana; P. Smitha; Chengcheng Fei; Raghavan Srinivasan. A Comparative Evaluation of the Performance of CHIRPS and CFSR Data for Different Climate Zones Using the SWAT Model. Remote Sensing 2020, 12, 3088 .

AMA Style

Yeganantham Dhanesh, V. Bindhu, Javier Senent-Aparicio, Tássia Brighenti, Essayas Ayana, P. Smitha, Chengcheng Fei, Raghavan Srinivasan. A Comparative Evaluation of the Performance of CHIRPS and CFSR Data for Different Climate Zones Using the SWAT Model. Remote Sensing. 2020; 12 (18):3088.

Chicago/Turabian Style

Yeganantham Dhanesh; V. Bindhu; Javier Senent-Aparicio; Tássia Brighenti; Essayas Ayana; P. Smitha; Chengcheng Fei; Raghavan Srinivasan. 2020. "A Comparative Evaluation of the Performance of CHIRPS and CFSR Data for Different Climate Zones Using the SWAT Model." Remote Sensing 12, no. 18: 3088.

Journal article
Published: 08 June 2020 in Remote Sensing
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Gridded precipitation products (GPPs) with wide spatial coverage and easy accessibility are well recognized as a supplement to ground-based observations for various hydrological applications. The error properties of satellite rainfall products vary as a function of rainfall intensity, climate region, altitude, and land surface conditions—all factors that must be addressed prior to any application. Therefore, this study aims to evaluate four commonly used GPPs: the Climate Prediction Center (CPC) Unified Gauge-Based Analysis of Global Daily Precipitation, the Climate Prediction Center Morphing (CMORPH) technique, the Tropical Rainfall Measuring Mission (TRMM) 3B42, and the Global Satellite Mapping of Precipitation (GSMaP), using data collected in the period 1998–2006 at different spatial and temporal scales. Furthermore, this study investigates the hydrological performance of these products against the 175 rain gauges placed across the whole Mekong River Basin (MRB) using a set of statistical indicators, along with the Soil and Water Assessment Tool (SWAT) model. The results from the analysis indicate that TRMM has the best performance at the annual, seasonal, and monthly scales, but at the daily scale, CPC and GSMaP are revealed to be the more accurate option for the Upper MRB. The hydrological evaluation results at the daily scale further suggest that the TRMM is the more accurate option for hydrological performance in the Lower MRB, and CPC shows the best performance in the Upper MRB. Our study is the first attempt to use distinct suggested GPPs for each individual sub-region to evaluate the water balance components in order to provide better references for the assessment and management of basin water resources in data-scarce regions, suggesting strong capabilities for utilizing publicly available GPPs in hydrological applications.

ACS Style

Kha Dang Dinh; Tran Ngoc Anh; Nhu Y Nguyen; Du Duong Bui; Raghavan Srinivasan. Evaluation of Grid-Based Rainfall Products and Water Balances over the Mekong River Basin. Remote Sensing 2020, 12, 1858 .

AMA Style

Kha Dang Dinh, Tran Ngoc Anh, Nhu Y Nguyen, Du Duong Bui, Raghavan Srinivasan. Evaluation of Grid-Based Rainfall Products and Water Balances over the Mekong River Basin. Remote Sensing. 2020; 12 (11):1858.

Chicago/Turabian Style

Kha Dang Dinh; Tran Ngoc Anh; Nhu Y Nguyen; Du Duong Bui; Raghavan Srinivasan. 2020. "Evaluation of Grid-Based Rainfall Products and Water Balances over the Mekong River Basin." Remote Sensing 12, no. 11: 1858.

Journal article
Published: 29 May 2020 in Weather and Climate Extremes
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Understanding the spatio-temporal distribution of rainfall characteristics has a major role in assessing the availability of water resources over a catchment. Therefore, it is necessary to understand the changes in rainfall characteristics using gridded precipitation data and robust statistical analysis for making decisions. In this study, the trends in rainfall and rainfall extremes over the Nagavali and Vamsadhara river basins are studied at three time steps (long-term-1901-2018, pre-1950, and post-1950) with four different Mann-Kendall (MK) tests using daily gridded rainfall data of 118 years (1901–2018). The spatial patterns of the trends are evaluated with the kriging interpolation method. Magnitude in rainfall and rainfall extremes (CDD, CWD, PRCPTOT, R10MM, R20MM, R40MM, R95PTOT, RX1DAY, and RX5DAY) are analyzed using the Sen's slope method. Except in the monsoon season, a decreasing trend is observed in all the rainfall extremes in post-1950 compared to pre-1950 period. Whereas, in the monsoon an increasing trend is observed for the extremes in post-1950 period. Overall period (i.e, 1901–2018) an increasing trend is observed for rainfall and rainfall extremes in the pre-monsoon (March–May), monsoon (June–Sep) seasons and a decreasing trend in the winter season (Dec–Feb) for both the basins. No obvious trends are evident in the post-monsoon season (Oct–Nov). At the annual scale, rainfall and rainfall extremes exhibited an increasing trend. Overall, the Nagavali basin experienced more extreme rainfall events indicating the higher vulnerability of floods while the middle and lower portions of the Vamsadhara basin shown increase in extremes. When linked with hydrological analysis, insights gained from this study are useful for flood vulnerability mapping and risk assessment for both the basins.

ACS Style

G. Venkata Rao; K. Venkata Reddy; Raghavan Srinivasan; Venkataramana Sridhar; N.V. Umamahesh; Deva Pratap. Spatio-temporal analysis of rainfall extremes in the flood-prone Nagavali and Vamsadhara Basins in eastern India. Weather and Climate Extremes 2020, 29, 100265 .

AMA Style

G. Venkata Rao, K. Venkata Reddy, Raghavan Srinivasan, Venkataramana Sridhar, N.V. Umamahesh, Deva Pratap. Spatio-temporal analysis of rainfall extremes in the flood-prone Nagavali and Vamsadhara Basins in eastern India. Weather and Climate Extremes. 2020; 29 ():100265.

Chicago/Turabian Style

G. Venkata Rao; K. Venkata Reddy; Raghavan Srinivasan; Venkataramana Sridhar; N.V. Umamahesh; Deva Pratap. 2020. "Spatio-temporal analysis of rainfall extremes in the flood-prone Nagavali and Vamsadhara Basins in eastern India." Weather and Climate Extremes 29, no. : 100265.

Journal article
Published: 04 April 2020 in Ecological Engineering
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Lake Riogrande II, located in the central region of the Colombian Andes, has eutrophication due to a progressive increase of runoff pollution from upstream intensive dairy cattle and agricultural activities in the watershed. Public and private entities have invested in programs aimed at adopting the best agricultural management practices (BMP). BMP is a general formulation of recommended criteria and, therefore, not universally fit all problems. For example, the corrective measures taken so far demonstrate difficulties in selecting and allocating BMPs aligned to the space-time hydrological variability within the watershed. This research analyses the spatio-temporal dynamics of BMP pollution patterns. The study is built on the concept of critical source areas of runoff pollution from agricultural practices in the Colombia Andes. Fieldwork was conducted with the participation of farmers to collect spatial data of the current management operations for potato (Solanum tuberosum), tree tomato (Solanum betaceum), and dairy agriculture. A Soil Water Assessment model is used to simulate agricultural and hydrological processes. The model was calibrated using observed discharge, nitrate-N (NO3—N), and soluble phosphorus (P) concentrations at a monthly scale. The origin of pollution at the catchment scale was used applying the critical source areas (CSAs) method. This paper proposes for this analysis a new spatio-temporal CSA index (ST-CSA) to represent the behavior of the CSAs simultaneously in space and time. For this, several aggregated CSA in time were analyzed for monthly and annual time steps. Results indicate that there is an essential difference in the aggregation of CSA in time, and pollution location changes significantly using the ST-CSA. As expected, the highest number of CSAs occurs during the rainy months. However, these CSAs are located in the region with the lowest precipitation levels in the agricultural areas dominated by potato, tree tomato, and dairy agriculture located within the watershed. These areas vary significantly from 24.07% of the entire area of the basin (1034.348 km2), and it could reach a maximum value of 61.78%. Despite the model uncertainties, the results highlight the importance of identifying spatio-temporal CSAs to select BMPs with the highest potential of nitrogen and phosphorus losses reduction - such as the adaptation of fertilization schedules - applicable to the study watershed.

ACS Style

Natalia Uribe; Raghavan Srinivasan; Gerald Corzo; David Arango; Dimitri Solomatine. Spatio-temporal critical source area patterns of runoff pollution from agricultural practices in the Colombian Andes. Ecological Engineering 2020, 149, 105810 .

AMA Style

Natalia Uribe, Raghavan Srinivasan, Gerald Corzo, David Arango, Dimitri Solomatine. Spatio-temporal critical source area patterns of runoff pollution from agricultural practices in the Colombian Andes. Ecological Engineering. 2020; 149 ():105810.

Chicago/Turabian Style

Natalia Uribe; Raghavan Srinivasan; Gerald Corzo; David Arango; Dimitri Solomatine. 2020. "Spatio-temporal critical source area patterns of runoff pollution from agricultural practices in the Colombian Andes." Ecological Engineering 149, no. : 105810.

Journal article
Published: 19 November 2019 in Remote Sensing
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Satellite-based precipitation is an essential tool for regional water resource applications that requires frequent observations of meteorological forcing, particularly in areas that have sparse rain gauge networks. To fully realize the utility of remotely sensed precipitation products in watershed modeling and decision-making, a thorough evaluation of the accuracy of satellite-based rainfall and regional gauge network estimates is needed. In this study, Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42 v.7 and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) daily rainfall estimates were compared with daily rain gauge observations from 2000 to 2014 in the Lower Mekong River Basin (LMRB) in Southeast Asia. Monthly, seasonal, and annual comparisons were performed, which included the calculations of correlation coefficient, coefficient of determination, bias, root mean square error (RMSE), and mean absolute error (MAE). Our validation test showed TMPA to correctly detect precipitation or no-precipitation 64.9% of all days and CHIRPS 66.8% of all days, compared to daily in-situ rainfall measurements. The accuracy of the satellite-based products varied greatly between the wet and dry seasons. Both TMPA and CHIRPS showed higher correlation with in-situ data during the wet season (June–September) as compared to the dry season (November–January). Additionally, both performed better on a monthly than an annual time-scale when compared to in-situ data. The satellite-based products showed wet biases during months that received higher cumulative precipitation. Based on a spatial correlation analysis, the average r-value of CHIRPS was much higher than TMPA across the basin. CHIRPS correlated better than TMPA at lower elevations and for monthly rainfall accumulation less than 500 mm. While both satellite-based products performed well, as compared to rain gauge measurements, the present research shows that CHIRPS might be better at representing precipitation over the LMRB than TMPA.

ACS Style

Chelsea Dandridge; Venkat Lakshmi; John Bolten; Raghavan Srinivasan. Evaluation of Satellite-Based Rainfall Estimates in the Lower Mekong River Basin (Southeast Asia). Remote Sensing 2019, 11, 2709 .

AMA Style

Chelsea Dandridge, Venkat Lakshmi, John Bolten, Raghavan Srinivasan. Evaluation of Satellite-Based Rainfall Estimates in the Lower Mekong River Basin (Southeast Asia). Remote Sensing. 2019; 11 (22):2709.

Chicago/Turabian Style

Chelsea Dandridge; Venkat Lakshmi; John Bolten; Raghavan Srinivasan. 2019. "Evaluation of Satellite-Based Rainfall Estimates in the Lower Mekong River Basin (Southeast Asia)." Remote Sensing 11, no. 22: 2709.

Journal article
Published: 14 November 2019 in International Journal of Applied Earth Observation and Geoinformation
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Leaf Area Index (LAI) models that consider all phenological stages have not been developed for the Caatinga, the largest seasonally dry tropical forest in South America. LAI models that are currently used show moderate to high covariance when compared to in situ data, but they often lack accuracy in the whole spectra of possible values and do not consider the impact that the stems and branches have over LAI estimates, which is of great influence in the Caatinga. In this study, we develop and assess PAI (Plant Area Index) and LAI models by using ground-based measurements and satellite (Landsat) data. The objective of this study was to create and test new empirical models using a multi-year and multi-source of reflectance data. The study was based on measurements of photosynthetic photon flux density (PPFD) from above and below the canopy during the periods of 2011–2012 and 2016–2018. Through iterative processing, we obtained more than a million candidate models for estimating PAI and LAI. To clean up the small discrepancies in the extremes of each interpolated series, we smoothed out the dataset by fitting a logarithmic equation with the PAI data and the inverse contribution of WAI (Wood Area Index) to PAI, that is the portion of PAI that is actually LAI (LAIC). LAIC can be calculated as follows: LAIC=1-WAI/PAI). We subtracted the WAI values from the PAI to develop our in situ LAI dataset that was used for further analysis. Our in situ dataset was also used as a reference to compare our models with four other models used for the Caatinga, as well as the MODIS-derived LAI products (MCD15A3H/A2H). Our main findings were as follows: (i) Six models use NDVI (Normalized Difference Vegetation Index), SAVI (Soil-Adjusted Vegetation Index) and EVI (Enhanced Vegetation Index) as input, and performed well, with r2 ranging from 0.77 to 0.79 (PAI) and 0.76 to 0.81 (LAI), and RMSE with a minimum of 0.41 m2 m−2 (PAI) and 0.40 m2 m−2 (LAI). The SAVI models showed values 20% and 32% (PAI), and 21% and 15% (LAI) smaller than those found for the models that use EVI and NDVI, respectively; (ii) the other models (ten) use only two bands, and in contrast to the first six models, these new models may abstract other physical processes and components, such as leaves etiolation and increasing protochlorophyll. The developed models used the near-infrared band, and they varied only in relation to the inclusion of the red, green, and blue bands. (iii) All previously published models and MODIS-LAI underperformed against our calibrated models. Our study was able to provide several PAI and LAI models that realistically represent the phenology of the Caatinga.

ACS Style

Rodrigo De Queiroga Miranda; Rodolfo Luiz Bezerra Nóbrega; Magna Soelma Beserra de Moura; Srinivasan Raghavan; Josiclêda Domiciano Galvíncio. Realistic and simplified models of plant and leaf area indices for a seasonally dry tropical forest. International Journal of Applied Earth Observation and Geoinformation 2019, 85, 101992 .

AMA Style

Rodrigo De Queiroga Miranda, Rodolfo Luiz Bezerra Nóbrega, Magna Soelma Beserra de Moura, Srinivasan Raghavan, Josiclêda Domiciano Galvíncio. Realistic and simplified models of plant and leaf area indices for a seasonally dry tropical forest. International Journal of Applied Earth Observation and Geoinformation. 2019; 85 ():101992.

Chicago/Turabian Style

Rodrigo De Queiroga Miranda; Rodolfo Luiz Bezerra Nóbrega; Magna Soelma Beserra de Moura; Srinivasan Raghavan; Josiclêda Domiciano Galvíncio. 2019. "Realistic and simplified models of plant and leaf area indices for a seasonally dry tropical forest." International Journal of Applied Earth Observation and Geoinformation 85, no. : 101992.

Journal article
Published: 01 October 2019 in Environmental Modelling & Software
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Spencer McDonald; Ibrahim Nourein Mohammed; John D. Bolten; Sarva Pulla; Chinaporn Meechaiya; Amanda Markert; E. James Nelson; Raghavan Srinivasan; Venkat Lakshmi. Web-based decision support system tools: The Soil and Water Assessment Tool Online visualization and analyses (SWATOnline) and NASA earth observation data downloading and reformatting tool (NASAaccess). Environmental Modelling & Software 2019, 120, 1 .

AMA Style

Spencer McDonald, Ibrahim Nourein Mohammed, John D. Bolten, Sarva Pulla, Chinaporn Meechaiya, Amanda Markert, E. James Nelson, Raghavan Srinivasan, Venkat Lakshmi. Web-based decision support system tools: The Soil and Water Assessment Tool Online visualization and analyses (SWATOnline) and NASA earth observation data downloading and reformatting tool (NASAaccess). Environmental Modelling & Software. 2019; 120 ():1.

Chicago/Turabian Style

Spencer McDonald; Ibrahim Nourein Mohammed; John D. Bolten; Sarva Pulla; Chinaporn Meechaiya; Amanda Markert; E. James Nelson; Raghavan Srinivasan; Venkat Lakshmi. 2019. "Web-based decision support system tools: The Soil and Water Assessment Tool Online visualization and analyses (SWATOnline) and NASA earth observation data downloading and reformatting tool (NASAaccess)." Environmental Modelling & Software 120, no. : 1.

Journal article
Published: 24 September 2019 in Agronomy
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Best management practices (BMPs) provide a feasible solution for non-point source pollution problems. High sediment and nutrient yields without retention control result in environmental deterioration of surrounding areas. In the present study, the soil and water assessment tool (SWAT) model was developed for El Beal watershed, an anthropogenic and ungauged basin located in the southeast of Spain that drains into a coastal lagoon of high environmental value. The effectiveness of five BMPs (contour planting, filter strips, reforestation, fertilizer application and check dam restoration) was quantified, both individually and in combination, to test their impact on sediment and nutrient reduction. For calibration and validation processes, actual evapotranspiration (AET) data obtained from a remote sensing dataset called Global Land Evaporation Amsterdam Model (GLEAM) were used. The SWAT model achieved good performance in the calibration period, with statistical values of 0.78 for Kling–Gupta efficiency (KGE), 0.81 for coefficient of determination (R2), 0.58 for Nash–Sutcliffe efficiency (NSE) and 3.9% for percent bias (PBIAS), as well as in the validation period (KGE = 0.67, R2 = 0.83, NS = 0.53 and PBIAS = −25.3%). The results show that check dam restoration is the most effective BMP with a reduction of 90% in sediment yield (S), 15% in total nitrogen (TN) and 22% in total phosphorus (TP) at the watershed scale, followed by reforestation (S = 27%, TN = 16% and TP = 20%). All effectiveness values improved when BMPs were assessed in combination. The outcome of this study could provide guidance for decision makers in developing possible solutions for environmental problems in a coastal lagoon.

ACS Style

Adrián López-Ballesteros; Javier Senent-Aparicio; Raghavan Srinivasan; Julio Pérez-Sánchez. Assessing the Impact of Best Management Practices in a Highly Anthropogenic and Ungauged Watershed Using the SWAT Model: A Case Study in the El Beal Watershed (Southeast Spain). Agronomy 2019, 9, 576 .

AMA Style

Adrián López-Ballesteros, Javier Senent-Aparicio, Raghavan Srinivasan, Julio Pérez-Sánchez. Assessing the Impact of Best Management Practices in a Highly Anthropogenic and Ungauged Watershed Using the SWAT Model: A Case Study in the El Beal Watershed (Southeast Spain). Agronomy. 2019; 9 (10):576.

Chicago/Turabian Style

Adrián López-Ballesteros; Javier Senent-Aparicio; Raghavan Srinivasan; Julio Pérez-Sánchez. 2019. "Assessing the Impact of Best Management Practices in a Highly Anthropogenic and Ungauged Watershed Using the SWAT Model: A Case Study in the El Beal Watershed (Southeast Spain)." Agronomy 9, no. 10: 576.

Journal article
Published: 14 August 2019 in Water
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For almost 30 years, the Soil and Water Assessment Tool (SWAT) has been successfully implemented to address issues around various scientific subjects in the world. On the other hand, it has been reaching to the limit of potential flexibility in further development by the current structure. The new generation SWAT, dubbed SWAT+, was released recently with entirely new coding features. SWAT+ is designed to have far more advanced functions and capacities to handle challenging watershed modeling tasks for hydrologic and water quality processes. However, it is still inevitable to conduct model calibration before the SWAT+ model is applied to engineering projects and research programs. The primary goal of this study is to develop an open-source, easy-to-operate automatic calibration tool for SWAT+, dubbed IPEAT+ (Integrated Parameter Estimation and Uncertainty Analysis Tool Plus). There are four major advantages: (i) Open-source code to general users; (ii) compiled and integrated directly with SWAT+ source code as a single executable; (iii) supported by the SWAT developer group; and, (iv) built with efficient optimization technique. The coupling work between IPEAT+ and SWAT+ is fairly simple, which can be conducted by users with minor efforts. IPEAT+ will be regularly updated with the latest SWAT+ revision. If users would like to integrate IPEAT+ with various versions of SWAT+, only few lines in the SWAT+ source code are required to be updated. IPEAT+ is the first automatic calibration tool integrated with SWAT+ source code. Users can take advantage of the tool to pursue more cutting-edge and forward-thinking scientific questions.

ACS Style

Haw Yen; Seonggyu Park; Jeffrey G. Arnold; Raghavan Srinivasan; Celray James Chawanda; Ruoyu Wang; Qingyu Feng; Jingwen Wu; Chiyuan Miao; Katrin Bieger; Prasad Daggupati; Ann Van Griensven; Latif Kalin; Sangchul Lee; Aleksey Y. Sheshukov; Michael J. White; Yongping Yuan; In-Young Yeo; Minghua Zhang; Xuesong Zhang. IPEAT+: A Built-In Optimization and Automatic Calibration Tool of SWAT+. Water 2019, 11, 1681 .

AMA Style

Haw Yen, Seonggyu Park, Jeffrey G. Arnold, Raghavan Srinivasan, Celray James Chawanda, Ruoyu Wang, Qingyu Feng, Jingwen Wu, Chiyuan Miao, Katrin Bieger, Prasad Daggupati, Ann Van Griensven, Latif Kalin, Sangchul Lee, Aleksey Y. Sheshukov, Michael J. White, Yongping Yuan, In-Young Yeo, Minghua Zhang, Xuesong Zhang. IPEAT+: A Built-In Optimization and Automatic Calibration Tool of SWAT+. Water. 2019; 11 (8):1681.

Chicago/Turabian Style

Haw Yen; Seonggyu Park; Jeffrey G. Arnold; Raghavan Srinivasan; Celray James Chawanda; Ruoyu Wang; Qingyu Feng; Jingwen Wu; Chiyuan Miao; Katrin Bieger; Prasad Daggupati; Ann Van Griensven; Latif Kalin; Sangchul Lee; Aleksey Y. Sheshukov; Michael J. White; Yongping Yuan; In-Young Yeo; Minghua Zhang; Xuesong Zhang. 2019. "IPEAT+: A Built-In Optimization and Automatic Calibration Tool of SWAT+." Water 11, no. 8: 1681.

Review
Published: 13 August 2019 in Hydrological Sciences Journal
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Tássia Mattos Brighenti; Nadia Bernardi Bonumá; Raghavan Srinivasan; Pedro Luiz Borges Chaffe. Simulating sub-daily hydrological process with SWAT: a review. Hydrological Sciences Journal 2019, 64, 1415 -1423.

AMA Style

Tássia Mattos Brighenti, Nadia Bernardi Bonumá, Raghavan Srinivasan, Pedro Luiz Borges Chaffe. Simulating sub-daily hydrological process with SWAT: a review. Hydrological Sciences Journal. 2019; 64 (12):1415-1423.

Chicago/Turabian Style

Tássia Mattos Brighenti; Nadia Bernardi Bonumá; Raghavan Srinivasan; Pedro Luiz Borges Chaffe. 2019. "Simulating sub-daily hydrological process with SWAT: a review." Hydrological Sciences Journal 64, no. 12: 1415-1423.

Journal article
Published: 20 May 2019 in Sustainability
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Water availability is essential for the appropriate analysis of its sustainable management. We performed a comparative study of six hydrological balance models (Témez, ABCD, GR2M, AWBM, GUO-5p, and Thornthwaite-Mather) in several basins with different climatic conditions within Spain in the 1977–2010 period. We applied six statistical indices to compare the results of the models: the Akaike information criterion (AIC), the Bayesian information criterion (BIC), Nash–Sutcliffe model efficiency coefficient (NSE), coefficient of determination (R2), percent bias (PBIAS), and the relative error between observed and simulated run-off volumes (REV). Furthermore, we applied the FITEVAL software to determine the uncertainty of the model. The results show that when the catchments are more humid the obtained results are better. The GR2M model gave the best fit in peninsular Spain in a UNEP aridity index framework above 1, and NSE values above 0.75 in a 95% confidence interval classify GR2M as very good for humid watersheds. The use of REV is also a key index in the assessment of the margin of error. Flow duration curves show good performance in the probabilities of exceedance lower than 80% in wet watersheds and deviations in low streamflows account for less than 5% of the total streamflow.

ACS Style

Julio Pérez-Sánchez; Javier Senent-Aparicio; Francisco Segura-Méndez; David Pulido-Velazquez; Raghavan Srinivasan. Evaluating Hydrological Models for Deriving Water Resources in Peninsular Spain. Sustainability 2019, 11, 2872 .

AMA Style

Julio Pérez-Sánchez, Javier Senent-Aparicio, Francisco Segura-Méndez, David Pulido-Velazquez, Raghavan Srinivasan. Evaluating Hydrological Models for Deriving Water Resources in Peninsular Spain. Sustainability. 2019; 11 (10):2872.

Chicago/Turabian Style

Julio Pérez-Sánchez; Javier Senent-Aparicio; Francisco Segura-Méndez; David Pulido-Velazquez; Raghavan Srinivasan. 2019. "Evaluating Hydrological Models for Deriving Water Resources in Peninsular Spain." Sustainability 11, no. 10: 2872.

Journal article
Published: 13 May 2019 in Forests
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In the Lower Mekong River Basin (LMB), deforestation rates are some of the highest in the world as land is converted primarily into intensive agriculture and plantations. While this has been a key for the region’s economic development, rural populations dependent on the freshwater water resources that support their fishing and agriculture industries are increasingly vulnerable to the impacts of flood, drought and non-point source pollution. Impacts of deforestation on ecosystem services (ES) including hydrological ES that control the availability and quality of fresh water across the landscape, regulating floods and droughts, soil erosion and non-point source pollution are known. Despite this understanding at the hillslope level, few studies have been able to quantify the impact of wide-scale deforestation on larger tropical watersheds. This study introduces a new methodology to quantify the impact of deforestation on water-based ES in the LMB with a focus on Cambodia by combining spatial datasets on forest loss from remote sensing and spatially-explicit hydrological modeling. Numerous global and regional remote sensing products are synthesized to develop detailed land use change maps for 2001 to 2013 for the LMB, which are then used as inputs into a hydrological model to develop unique spatial datasets that map ES changes due to deforestation across the LMB. The results point to a clear correlation between forest loss and surface runoff, with a weaker but upward trending relationship between forest loss and sediment yield. This resulted in increased river discharge for 17 of the 22 watersheds, and increased sediment for all 22 watersheds. While there is considerable variability between watersheds, these results could be helpful for prioritizing interventions to decrease deforestation by highlighting which areas have experienced the greatest change in water-based ES provision. These results are also presented in a web-based platform called the Watershed Ecosystem Service Tool.

ACS Style

Michael S. Netzer; Gabriel Sidman; Timothy R.H. Pearson; Sarah M. Walker; Raghavan Srinivasan. Combining Global Remote Sensing Products with Hydrological Modeling to Measure the Impact of Tropical Forest Loss on Water-Based Ecosystem Services. Forests 2019, 10, 413 .

AMA Style

Michael S. Netzer, Gabriel Sidman, Timothy R.H. Pearson, Sarah M. Walker, Raghavan Srinivasan. Combining Global Remote Sensing Products with Hydrological Modeling to Measure the Impact of Tropical Forest Loss on Water-Based Ecosystem Services. Forests. 2019; 10 (5):413.

Chicago/Turabian Style

Michael S. Netzer; Gabriel Sidman; Timothy R.H. Pearson; Sarah M. Walker; Raghavan Srinivasan. 2019. "Combining Global Remote Sensing Products with Hydrological Modeling to Measure the Impact of Tropical Forest Loss on Water-Based Ecosystem Services." Forests 10, no. 5: 413.