Assessing the Effectiveness of the Use of the InVEST Annual Water Yield Model for the Rivers of Colombia: A Case Study of the Meta River Basin

Abstract

This paper presents the results of one of the hydrological models, the InVEST “Annual Water Yield” (InVEST–AWY), applied to the Meta River basin in Colombia, which covers an area of 113,981 km². The study evaluates the performance of the model in different subbasins of the Meta River basin. The model’s accuracy was assessed using different statistical measures, including Nash–Sutcliffe Efficiency (NSE) coefficient, Root Mean Square Error (RMSE), correlation coefficients for the calibration (rcal) and validation (rval) periods. The overall performance of the model in the Meta River basin is relatively poor as indicated by the low NSE value of 0.07 and high RMSE value of 1071.61. In addition, the model explains only a 7% of the variance in the observed data. The sensitivity analysis revealed that a 30% reduction in crop coefficient (Kc) values would result in a 10.7% decrease in water yield. The model estimated, for example, the annual average water yield of the river in 2018 as 1.98 × 1011 m3/year or 6273.4 m3/s, which is 1.3% lower than the reported value. The upper Meta River subbasin shows the highest NSE value (0.49), indicating a good result between observed and simulated water discharge. In contrast, the South Cravo River subbasin shows a negative NSE value of −1.29, indicating poor model performance. The Yucao River subbasin and the upper Casanare River subbasin also show lower NSE values compared to the upper Meta River subbasin, indicating less accurate model performance in these subbasins. The correlation coefficients in calibration (rcal) and validation (rval) for the upper Meta River, Yucao River, South Cravo River, and upper Casanare River subbasins were 0.79 and 0.83, 0.4 and 0.22, 0.5 and −0.25, and 0 and 0.18, respectively. These results provide useful insights into the limitations for the proper use of the InVEST–AWY model in Colombia. This study is the first to use the InVEST–AWY model on a large scale in the territory of Colombia, allowing to evaluate its effectiveness in hydrological modeling for water management.

Effect of LULC Changes on Annual Water Yield in the Urban Section of the Chili River, Arequipa, Using the InVEST Model

“…Several studies have carried out sensitivity analyses [3,58] on the model's results which allows them to be solid and reliable, comparing them to real values. Additionally, scenario analysis such as in the study carried out by [40] allows for the prediction of water yield behavior in future years.…”

“…The methodology flow chart (Figure 2) was adapted from the study conducted by [3]. The same procedure was applied for both years, 1984 and 2022, with the inputs of the root boundary layer depth, the study area and the available water content for plants being constant parameters for both years when calculating water performance.…”

“…Urban rivers are ecological corridors that maintain landscape connectivity, protect biodiversity and provide a multiplicity of ecosystem services (ESs) for human health and human well-being [1][2][3], increasing cities' global levels of resilience against climate change [4,5].…”

“…Over the years, population growth, climate change impacts and the change in land use [3,6,7] have generated a larger area composed of waterproof surfaces, which translates into limited humidity exchange, temperature increase [8] and a negative impact on the ESs related to urban rivers as hydric resources. Deforestation and agricultural land expansion cause an increase in annual runoff, evapotranspiration, river flow, groundwater depletion and lateral flow [9].…”

Predictive Assessment of Climate Change Impact on Water Yield in the Meta River Basin, Colombia: An InVEST Model Application

“…Despite limitations assessing model performance, several studies have shown that relatively simple models with limited data requirements can credibly simulate flows and water balance components in large, data-poor basins. Valencia et al [9] used the annual water yield model from the INVEST package to quantify current water yields in specific subbasins in the Meta River basin, Colombia. The study [10] also demonstrated the application of a distributed hydrological model like MIKE-SHE in data-scarce watersheds to assess climate change impacts on water resources, using limited meteorological and hydrological data for model input.…”