A framework model to integrate sources and pathways in the assessment of river water pollution.

Metal and nutrient pollution, soil erosion, and alterations in climate and hydrology are prevalent issues that impact the water quality of riverine systems. However, integrated approaches to assess and isolate causes and paths of river water pollution are scarce, especially in the case of watersheds impacted by multiple hazardous activities. Therefore, a framework model for investigating the multiple sources of river water pollution was developed. The chosen study area was the Paraopeba River basin located in the Minas Gerais, Brazil. Besides multiple agriculture, industrial, and urban pollution sources, this region was profoundly affected by the rupture of the B1 tailings dam (in January 2019) at the Córrego do Feijão mine, resulting in the release of metal-rich waste. Considering this situation, thirty-nine physicochemical and hydromorphological parameters were examined in the Paraopeba River basin, in the 2019-2023 period. The analysis involved various statistical techniques, including bivariate and multivariate methods such as correlation analysis, principal component analysis, and clustering. The Paraopeba River was mainly impacted by metal contamination resulting from the dam collapse, whereas nutrient contamination, mainly from urban and industrial discharges, predominantly affected its tributaries. Additionally, the elevated concentrations of aluminum, iron, nitrate, and sulfate in both main river and tributaries can be attributed to diffuse and point source pollution. In terms of hydromorphology and soil type, the interaction between woody vegetation and erosion-resistant soils, especially latosols, contributes to the stability of riverbanks in the main river. Meanwhile, in the tributaries, the presence of neosols and sparse vegetation in urbanized areas promoted riverbank erosion potentially amplifying pollution. While the study was conducted in a particular watershed, the findings are based on a methodology that can be applied universally. Hence, the insights on surface water quality from this research can be a valuable resource for researchers studying watersheds with diverse pollution sources.

Hydrologic Modeling for Sustainable Water Resources Management in Urbanized Karst Areas.

The potential of karst aquifers as a drinking water resource is substantial because of their large storage capacity gained in the course of carbonate dissolution. Carbonate dissolution and consequent development of preferential paths are also the reasons for the complex behavior of these aquifers as regards surface and underground flow. Hydrological modeling is therefore of paramount importance for an adequate assessment of flow components in catchments shaped on karsts. The cross tabulation of such components with geology, soils, and land use data in Geographic Information Systems helps decision makers to set up sustainable groundwater abstractions and allocate areas for storage of quality surface water, in the context of conjunctive water resources management. In the present study, a hydrologic modeling using the JAMS J2000 software was conducted in a karst area of Jequitiba River basin located near the Sete Lagoas town in the state of Minas Gerais, Brazil. The results revealed a very high surface water component explained by urbanization of Sete Lagoas, which hampers the recharge of 7.9 hm3 yr-1 of storm water. They also exposed a very large negative difference (-8.3 hm3 yr-1) between groundwater availability (6.3 hm3 yr-1) and current groundwater abstraction from the karst aquifer (14.6 hm3 yr-1), which is in keeping with previously reported water table declines around drilled wells that can reach 48 m in old wells used for public water supply. Artificial recharge of excess surface flow is not recommended within the urban areas, given the high risk of groundwater contamination with metals and hydrocarbons potentially transported in storm water, as well as development of suffosional sinkholes as a consequence of concentrated storm flow. The surface component could however be stored in small dams in forested areas from the catchment headwaters and diverted to the urban area to complement the drinking water supply. The percolation in soil was estimated to be high in areas used for agriculture and pastures. The implementation of correct fertilizing, management, and irrigation practices are considered crucial to attenuate potential contamination of groundwater and suffosional sinkhole development in these areas.

Development of a Hydrologic and Water Allocation Model to Assess Water Availability in the Sabor River Basin (Portugal).

The Sabor River basin is a large basin (3170 km2) located in the northeast of Portugal and used mostly for agroforestry. One problem this basin faces is a lack of water during the dry season, when there is a higher demand for water to irrigate crops. To solve this problem, the Portuguese government created a National Irrigation Program to finance new irrigation areas and improve existing ones. Consequently, it is necessary to evaluate the past and future water availability for agricultural and domestic consumption in the basin. This was done through the development of a hydrological and water allocation model. The Soil and Water Assessment Tool (SWAT) was used to model the hydrological processes that took place in the catchment between 1960 and 2008. The MIKE HYDRO Basin was used to simulate water allocation (irrigation and domestic consumption) in a historical view and under two scenarios. The historical view used the time period 1960-2008, and the two scenarios used the same time period but with an increase in the irrigated area. The first scenario simulated the irrigation of the total irrigable area that exists in the basin. The second scenario simulated a 29% increase in the olive grove area and a 24% decrease in the resident population, according to the projection for 2060. The results show that, in the historical view, the average annual water demand deficit was 31% for domestic consumption and 70% for irrigation, which represent 1372 × 103 m3 and 94 × 106 m3 of water, respectively. In the two scenarios, the water demand deficit increased to 37% for domestic consumption and 77% for irrigation. In the first scenario, the average annual water demand deficit was 183 × 106 m3 of water for irrigation. In the second scenario, the average annual water demand deficit was 385 × 103 m3 of water for domestic consumption, and 106 × 106 m3 of water for irrigating the expanded olive grove area. These results demonstrate that Portuguese farmers can use our model as a decision support tool to determine how much water needs to be stored to meet the present and future water demand.