Yaseen et al. (2025) Quantitative assessment of best management practices for soil and water conservation: A case study from the Tarquinia plain

Identification

• Journal: Agricultural Water Management
• Year: 2025
• Date: 2025-11-20
• Authors: Marwah Yaseen, Νικόλαος Μέλλιος, Alessandro Pagano, Ivan Portoghese, Raffaele Giordano, Vito Iacobellis, Aras Izzaddin, Silvia Vanino, Chrysi Laspidou
• DOI: 10.1016/j.agwat.2025.109952

Research Groups

• DICATECh, Politecnico di Bari, Bari, Italy
• Consiglio Nazionale Delle Ricerche – Istituto di Ricerca Sulle Acque (CNR-IRSA), Bari, Italy
• Civil Engineering Department, University of Thessaly, Volos, Greece
• Centro Agricoltura e Ambiente, Consiglio per La Ricerca in Agricoltura e L’Analisi Dell’Economia Agraria, Rome, Italy

Short Summary

This study utilized the Soil and Water Assessment Tool (SWAT) to quantitatively evaluate individual and combined Best Management Practices (BMPs) in the Tarquinia plain, Italy, demonstrating that combined BMPs significantly reduce river sediment load by up to 33.9 %, total nitrogen by 27 %, and total phosphorus by 27.5 %.

Objective

• To quantitatively assess the effectiveness of individual and combined Best Management Practices (BMPs) in reducing off-site impacts of soil erosion and nutrient pollution in the Tarquinia plain, Italy.
• To develop a replicable methodological framework that integrates hydrological modeling with stakeholder participation for co-design and co-assessment of BMPs.

Study Configuration

• Spatial Scale: Marta River watershed, covering 1.04762 x 10^9 m² (1047.62 km²), including Lake Bolsena (1.14 x 10^8 m²). The watershed was delineated into 28 sub-basins and 277 Hydrological Response Units (HRUs). Elevations range from 2 m to 983 m above sea level.
• Temporal Scale: 17-year simulation period (2004–2020), with a 2-year warm-up period. Calibration and validation periods varied for different parameters (e.g., flow discharge: calibration 2006–2015, validation 2016–2020; nitrate and total nitrogen: calibration 2013–2018, validation 2018–2019/2020).

Methodology and Data

• Models used: Soil and Water Assessment Tool (SWAT2012), Arc-SWAT (in Arc-GIS 10.6), SWAT-CUP software with SUFI-2 algorithm for calibration, validation, and sensitivity analysis.
• Data sources:
  • Digital Elevation Model (DEM): 30 m Shuttle Radar Topography Mission (SRTM) from USGS EarthExplorer.
  • Soil: 500 m Harmonized World Soil Database (HWSD).
  • Land-use: 100 m Corine Land Cover (CLC, 2018) from the European Environment Agency (EEA).
  • Weather data: Daily temperature, precipitation, solar radiation, relative humidity, and wind speed from 14 stations (2004–2020) and European daily gridded meteorological data (E-OBS).
  • River discharge: Monthly data (2004–2020) from 1 station (Regione Lazio - AGENZIA REGIONALE DI PROTEZIONE CIVILE).
  • Total Nitrogen (TN) and Nitrate: Monthly data (2004–2020) from 1 station (Arpa Lazio).
  • Agricultural management practices: Planting, fertilization, irrigation, and tillage data from local farmers and the 'North Coast' Reclamation Consortium.
  • Stakeholder input: Semi-structured interviews and participatory workshops for identifying challenges and selecting BMPs.

Main Results

• The Tarquinia Plain exhibits critical levels of soil erosion and nutrient loss, with a mean annual soil erosion rate of 0.833–0.859 kg m⁻² yr⁻¹ (8.33–8.59 t ha⁻¹ yr⁻¹), exceeding the European tolerable limit of 0.14 kg m⁻² yr⁻¹ (1.4 t ha⁻¹ yr⁻¹). Mean total nitrogen (TN) yield was 2.91 x 10⁻⁴ kg m⁻² yr⁻¹ (2.91 kg ha⁻¹ yr⁻¹) and total phosphorus (TP) yield was 2.84 x 10⁻⁴ kg m⁻² yr⁻¹ (2.84 kg ha⁻¹ yr⁻¹), higher than reported for other Mediterranean basins.
• Combined BMPs were the most effective, achieving:
  • Sediment load reduction of up to 33.9 % (from 2.627 x 10^6 kg y⁻¹ to 1.737 x 10^6 kg y⁻¹).
  • Total Nitrogen (TN) load reduction of up to 27 % (from 14,018.01 kg y⁻¹ to 10,236.62 kg y⁻¹).
  • Total Phosphorus (TP) load reduction of up to 27.5 % (from 108,464.81 kg y⁻¹ to 78,642.18 kg y⁻¹).
• Among individual BMPs, terracing performed best, achieving:
  • Sediment load reduction of up to 22 % (to 2.049 x 10^6 kg y⁻¹).
  • Total Nitrogen (TN) load reduction of up to 26.2 %.
  • Total Phosphorus (TP) load reduction of up to 22.7 %.
• Other individual BMPs (residue management, no-tillage, contour farming) also contributed to reductions, with varying effectiveness depending on the pollutant type.
• The SWAT model demonstrated good to very good performance for flow discharge (NSE > 0.66, R² > 0.71), nitrate (NSE > 0.7, R² > 0.78), and total nitrogen (NSE > 0.79, R² > 0.81) during calibration and validation.

Contributions

• Provides comprehensive quantitative insights into the efficacy of individual and combined Best Management Practices (BMPs) in reducing sediment and nutrient loading in a vulnerable Mediterranean agricultural watershed.
• Integrates hydrological modeling with participatory approaches, actively involving stakeholders in the co-design and co-assessment of BMPs, thereby bridging knowledge gaps and ensuring scientific soundness and social relevance.
• Offers a replicable methodological framework for identifying critical source areas and assessing BMP effectiveness, which can be applied to other watersheds globally to inform sustainable water management and climate adaptation strategies.
• Systematically evaluates the synergistic effects of combined BMPs, demonstrating their superior performance compared to individual practices in mitigating multiple forms of agricultural pollution.

Funding

• LENSES Project (PRIMA program – Grant Agreement n. 2041, https://www.lenses-prima.eu/)
• Partnership for Research and Innovation in the Mediterranean Area (PRIMA)

Citation

@article{Yaseen2025Quantitative,
  author = {Yaseen, Marwah and Μέλλιος, Νικόλαος and Pagano, Alessandro and Portoghese, Ivan and Giordano, Raffaele and Iacobellis, Vito and Izzaddin, Aras and Vanino, Silvia and Laspidou, Chrysi},
  title = {Quantitative assessment of best management practices for soil and water conservation: A case study from the Tarquinia plain},
  journal = {Agricultural Water Management},
  year = {2025},
  doi = {10.1016/j.agwat.2025.109952},
  url = {https://doi.org/10.1016/j.agwat.2025.109952}
}