Search Results (23)

In this study, we selected a series of pothole wetlands to investigate their nucleation, evolution, and recent anthropogenic degradation in the Alcores Depression (AD), southern Iberian Peninsula, where over 100 closed watersheds containing shallow, ephemeral water bodies up to 2 hm² have been identified. We surveyed the regional geological framework, utilized digital elevation models (DEMs), orthophotos, and aerial images since 1956. Moreover, we analyzed precipitation and temperature data in Seville from 1900 to 2024, collected hydrometeorological data since 1990 and modelled the water level evolution from 2002 to 2025 in a representative pothole in the area. Our observations indicate a flooded surface reduction by more than 90% from the 1950s to 2025. Climatic data reveal an increase in annual mean temperatures since 1960 and a sharp decline in annual precipitation since 2000. The AD’s inception due to tectonic isolation during the Quaternary favoured the formation of pothole wetlands in the floodplain. The reduction in the hydroperiod and wetland degradation was primarily due to agricultural expansion since 1950, which followed an increase in groundwater extraction and altered the original topography. Recently, decreased precipitation has exponentially accelerated the degradation and even the complete disappearance of many potholes. This study underscores the fragility of small wetlands in the Mediterranean basin and the critical role of human management in their preservation. Restoring these ecosystems could be a highly effective nature-based solution, especially in semi-arid climates like southern Spain. These prairie potholes are crucial for enhancing groundwater recharge, which is vital for maintaining water availability in regions with limited precipitation. By facilitating rainwater infiltration into the aquifer, recharge potholes increase groundwater levels. Additionally, they capture and store run-off during heavy rainfall, reducing the risk of flooding and soil erosion. Beyond their hydrological functions, these wetlands provide habitats that support biodiversity and promote ecological resilience, reinforcing the need for their protection and recovery. Full article

Knowledge of surface water extent is critical for ecological and disaster monitoring. However, surface water extraction from optical satellite imagery is challenging due to the impact of weather. Synthetic Aperture Radar (SAR) can penetrate cloud cover and has significant advantages for surface water mapping, but the classification accuracy might be limited by SAR’s inherent properties and land cover, which have similar backscatter to surface water. This study finds that the accuracy of surface water extraction at the Prairie Pothole Region (PPR) can be improved by combining interferometric coherence and backscatter for machine learning classification. This study performs time-series analysis on surface water and land to investigate their discrimination at different seasonal periods. The accuracy improvement of this method on Sentinel-1 images reached 10% during the seasons of fall and winter, where the combination of backscatter and coherence was proven to be efficient for separating water and land. Hence, our approaches of combining backscatter and coherence provide new insights for surface water extraction from SAR images in future studies. Full article

Conversion of grassland to cropland in the Prairie Pothole Region of North and South Dakota has many environmental consequences, including the loss of important migratory bird breeding grounds, increased agricultural chemical use, and release of sequestered carbon into the atmosphere. While conversion has negative ecological consequences, in years of high crop prices, cropland can generate higher returns than grassland, and farmers therefore face economic incentives for conversion in these years. However, recent research suggests that farmers may not convert land despite the economic incentives to do so. In this paper, we used the results of a framed economic experiment to explore the role of anticipated regret in farmers’ land conversion decisions. We used duration analysis to investigate the effect of anticipated regret salience on the risk of grass-to-crop land conversion and examined the regret participants express ex post about their land use decisions. Our results show that conversion risk from grassland to cropland was lower when anticipated regret was made salient than when it was not. Additionally, farmers expressed more regret about decisions to convert their land than when they left their land in grass. These results suggest that anticipated regret may play a role in farmers’ land conversion decisions, and that encouraging farmers to consider how they might feel about their decisions in the future may lead to lower rates of grass-to-crop conversion. We propose operational policy strategies based on our findings. Full article

Plant communities in North American prairie pothole wetlands vary depending on hydrology, salinity, and anthropogenic disturbance in and around the wetland. We assessed prairie pothole conditions on United States Fish and Wildlife Service fee-title lands in North Dakota and South Dakota to improve our understanding of current conditions and plant community composition. Species-level data were collected at 200 randomly chosen temporary and seasonal wetland sites located on native prairie remnants (n = 48) and previously cultivated lands that were reseeded into perennial grassland (n = 152). The majority of species surveyed appeared infrequently and were low in relative cover. The four most frequently observed species were introduced invasive species common to the Prairie Pothole Region of North America. Our results suggested relative cover of a few invasive species (i.e., Bromus inermis Leyss., Phalaris arundinacea L., and Typha ×glauca Godr. (pro sp.) [angustifolia or domingensis × latifolia]) affect patterns of plant community composition. Wetlands in native and reseeded grasslands possessed distinct plant community composition related to invasive species’ relative cover. Invasive species continue to be prevalent throughout the region and pose a major threat to biological diversity, even in protected native prairie remnants. Despite efforts to convert past agricultural land into biologically diverse, productive ecosystems, invasive species continue to dominate these landscapes and are becoming prominent in prairie potholes located in native areas. Full article

The homogenization of freshwater ecosystems and their biological communities has emerged as a prevalent and concerning phenomenon because of the loss of ecosystem multifunctionality. The millions of prairie-pothole wetlands scattered across the Prairie Pothole Region (hereafter PPR) provide critical ecosystem functions at local, regional, and continental scales. However, an estimated loss of 50% of historical wetlands and the widespread conversion of grasslands to cropland make the PPR a heavily modified landscape. Therefore, it is essential to understand the current and potential future stressors affecting prairie-pothole wetland ecosystems in order to conserve and restore their functions. Here, we describe a conceptual model that illustrates how (a) historical wetland losses, (b) anthropogenic landscape modifications, and (c) climate change interact and have altered the variability among remaining depressional wetland ecosystems (i.e., ecosystem homogenization) in the PPR. We reviewed the existing literature to provide examples of wetland ecosystem homogenization, provide implications for wetland management, and identify informational gaps that require further study. We found evidence for spatial, hydrological, chemical, and biological homogenization of prairie-pothole wetlands. Our findings indicate that the maintenance of wetland ecosystem multifunctionality is dependent on the preservation and restoration of heterogenous wetland complexes, especially the restoration of small wetland basins. Full article

Wetlands in the Prairie Pothole Region (PPR) of Canada and the United States represent a unique mapping challenge. They are dynamic both seasonally and year-to-year, are very small, and frequently altered by human activity. Many efforts have been made to estimate the loss of these important habitats but a high-quality inventory of pothole wetlands is needed for data-driven conservation and management of these resources. Typical landcover classifications using one or two image dates from optical or Synthetic Aperture Radar (SAR) Earth Observation (EO) systems often produce reasonable wetland inventories for less dynamic, forested landscapes, but will miss many of the temporary and seasonal wetlands in the PPR. Past studies have attempted to capture PPR wetland dynamics by using dense image stacks of optical or SAR data. We build upon previous work, using 2017–2020 Sentinel-2 imagery processed through the Google Earth Engine (GEE) cloud computing platform to capture seasonal flooding dynamics of wetlands in a prairie pothole wetland landscape in Alberta, Canada. Using 36 different image dates, wetland flood frequency (hydroperiod) was calculated by classifying water/flooding in each image date. This product along with the Global Ecosystem Dynamics Investigation (GEDI) Canopy Height Model (CHM) was then used to generate a seven-class wetland inventory with wetlands classified as areas with seasonal but not permanent water/flooding. Overall accuracies of the resulting inventory were between 95% and 96% based on comparisons with local photo-interpreted inventories at the Canadian Wetland Classification System class level, while wetlands themselves were classified with approximately 70% accuracy. The high overall accuracy is due, in part, to a dominance of uplands in the PPR. This relatively simple method of classifying water through time generates reliable wetland maps but is only applicable to ecosystems with open/non-complex wetland types and may be highly sensitive to the timing of cloud-free optical imagery that captures peak wetland flooding (usually post snow melt). Based on this work, we suggest that expensive field or photo-interpretation training data may not be needed to map wetlands in the PPR as self-labeling of flooded and non-flooded areas in a few Sentinel-2 images is sufficient to classify water through time. Our approach demonstrates a framework for the operational mapping of small, dynamic PPR wetlands that relies on open-access EO data and does not require costly, independent training data. It is an important step towards the effective conservation and management of PPR wetlands, providing an efficient method for baseline and ongoing mapping in these dynamic environments. Full article

Surface depressions are one of the important impact factors of hydrologic processes and catchment responses. However, in many hydrologic models, the influence of depressions is often simulated in a lumped manner, which results in the insufficient characterization of the filling–spilling–merging–splitting dynamics of depressions and the threshold behavior of the overland flow. The objective of the research reported in this paper is to improve the simulation of depression-influenced hydrologic processes by capturing the threshold control of depressions. To achieve this objective, a Depression-oriented Soil and Water Assessment Tool (SWAT-D) is developed. Specifically, the intrinsic changing patterns of contributing area and depression storage are first determined and further incorporated into the SWAT to simulate the filling–spilling of depressions and depression-influenced overland flow dynamics. The SWAT-D was applied to a depression-dominated watershed in the Prairie Pothole Region to evaluate its performance and capability. The simulated and observed hydrographs at the watershed outlet showed good agreement, with only a 7% deviation between the simulated and observed volumes of discharges in 2004. The NSE values for the simulated monthly average discharges during calibration and validation periods were 0.78 and 0.71, respectively, indicating the ability of the SWAT-D in reproducing the depression-influenced catchment responses. In addition, the SWAT-D was compared with other depression-oriented modeling techniques (i.e., the lumped depression approach and probability distribution models), and the comparisons emphasized the improvement of the SWAT-D and the importance of the research reported in this paper. Full article

The Prairie Pothole Region (PPR) contains numerous depressional wetlands known as potholes that provide habitats for waterfowl and other wetland-dependent species. Mapping these wetlands is essential for identifying viable waterfowl habitat and conservation planning scenarios, yet it is a challenging task due to the small size of the potholes, and the presence of emergent vegetation. This study develops an open-source process within the Google Earth Engine platform for mapping the spatial distribution of wetlands through the integration of Sentinel-1 C-band SAR (synthetic aperture radar) data with high-resolution (10-m) Sentinel-2 bands. We used two machine-learning algorithms (random forest (RF) and support vector machine (SVM)) to identify wetlands across the study area through supervised classification of the multisensor composite. We trained the algorithms with ground truth data provided through field studies and aerial photography. The accuracy was assessed by comparing the predicted and actual wetland and non-wetland classes using statistical coefficients (overall accuracy, Kappa, sensitivity, and specificity). For this purpose, we used four different out-of-sample test subsets, including the same year, next year, small vegetated, and small non-vegetated test sets to evaluate the methods on different spatial and temporal scales. The results were also compared to Landsat-derived JRC surface water products, and the Sentinel-2-derived normalized difference water index (NDWI). The wetlands derived from the RF model (overall accuracy 0.76 to 0.95) yielded favorable results, and outperformed the SVM, NDWI, and JRC products in all four testing subsets. To provide a further characterization of the potholes, the water bodies were stratified based on the presence of emergent vegetation using Sentinel-2-derived NDVI, and, after excluding permanent water bodies, using the JRC surface water product. The algorithm presented in the study is scalable and can be adopted for identifying wetlands in other regions of the world. Full article

The Prairie Pothole Region (PPR) of North America is an extremely important habitat for a diverse range of wetland ecosystems that provide a wealth of socio-economic value. This paper describes the ecological characteristics and importance of PPR wetlands and the use of remote sensing for mapping and monitoring applications. While there are comprehensive reviews for wetland remote sensing in recent publications, there is no comprehensive review about the use of remote sensing in the PPR. First, the PPR is described, including the wetland classification systems that have been used, the water regimes that control the surface water and water levels, and the soil and vegetation characteristics of the region. The tools and techniques that have been used in the PPR for analyses of geospatial data for wetland applications are described. Field observations for ground truth data are critical for good validation and accuracy assessment of the many products that are produced. Wetland classification approaches are reviewed, including Decision Trees, Machine Learning, and object versus pixel-based approaches. A comprehensive description of the remote sensing systems and data that have been employed by various studies in the PPR is provided. A wide range of data can be used for various applications, including passive optical data like aerial photographs or satellite-based, Earth-observation data. Both airborne and spaceborne lidar studies are described. A detailed description of Synthetic Aperture RADAR (SAR) data and research are provided. The state of the art is the use of multi-source data to achieve higher accuracies and hybrid approaches. Digital Surface Models are also being incorporated in geospatial analyses to separate forest and shrub and emergent systems based on vegetation height. Remote sensing provides a cost-effective mechanism for mapping and monitoring PPR wetlands, especially with the logistical difficulties and cost of field-based methods. The wetland characteristics of the PPR dictate the need for high resolution in both time and space, which is increasingly possible with the numerous and increasing remote sensing systems available and the trend to open-source data and tools. The fusion of multi-source remote sensing data via state-of-the-art machine learning is recommended for wetland applications in the PPR. The use of such data promotes flexibility for sensor addition, subtraction, or substitution as a function of application needs and potential cost restrictions. This is important in the PPR because of the challenges related to the highly dynamic nature of this unique region. Full article

The Prairie Pothole Region (PPR) is a biotically important region of grassland, wetland, and cropland that traverses the Canada-US border. Significant amounts of grasslands and wetlands within the PPR have been converted to croplands in recent years due to increasing demand for biofuels. We characterized land dynamics across the US portion of the PPR (US–PPR) using the USDA Crop Data Layer (CDL) for 2006–2018. We also conducted a comparative analysis between two epochs (1998–2007 & 2008–2017) of the CDL data time series in the North Dakotan portion of the US–PPR. The CDL revealed the western parts of the US–PPR have been dominated by grass/pasture, to the north it was spring wheat, to the east and southern half, soybeans dominated, and to the south it was corn (maize). Nonparametric trend analysis on the major crop and land cover types revealed statistically significant net decreases in the grass/pasture class between 2006 and 2018, which accounts for more than a quarter of grass/pasture area within the US–PPR. Other crops experiencing significant decreases included sunflower (-5%), winter wheat (-3%), spring wheat (-2%), and durum wheat (-1%). The combined coverage of corn and soybeans exhibited significant net increases in 23.5% of its cover; whereas, the individual significant net increases were 5% for corn and 11% for soybeans. Hotspots of increase in corn and soybeans were distributed across North and South Dakota. Other crop/land covers with huge significant increases include other hay/non-alfalfa (15%), and alfalfa (11%), which appear to be associated with the sharp increase in larger dairy operations, mostly in Minnesota. Wetland area increased 5% in the US–PPR, due to increased precipitation as well as inundation associated with Devils Lake in North Dakota. Hotspots of decreasing grass/pasture area were evident across the study area. Comparative trend analysis of two epochs (1998–2007 vs. 2008–2017) in North Dakota revealed that grass/pasture cover showed a negligible net trend (-0.3 %) between 1998 and 2007; whereas, there was a statistically significant decrease of more than 30% between 2008 and 2017. Combined coverage of corn and soybeans experienced statistically significant net increases in both epochs: 11% greater during 1998–2007 and 17% greater during 2008–2017. Recent sharp losses of grasslands and smaller wetlands combined the expansion of corn, soybeans, and alfalfa bode ill for wildlife habitat and require a re-examination of agricultural and energy policies that have encouraged these land transitions. Full article

Nest survival is most limited by nest predation, which often is increased by anthropogenic causes including habitat fragmentation, mesopredator release and predator subsidies. In mallards and other upland-nesting duck species in the North American prairies, the rate of nest survival is the vital rate most influential to population dynamics, with 15%–20% survival required for maintenance of stable populations. Predator removal during the nesting season has increased duck nest survival on township-sized (9324 ha) areas of agricultural ecosystems in eastern locations of the prairie pothole region (PPR). However, predator removal has not been evaluated in western parkland habitats of the PPR where three-dimensional structure of vegetation is considerably greater. During 2015–2017, we evaluated nest survival on control and predator-removal plots at two study areas in the parklands of central Alberta, Canada. In the second year of the study, we transposed predator removal to control for habitat effects. Estimates of 34-day nest survival did not significantly differ between trapped ( $\overline{x}$ = 20.9%, 95% CI = 13.2%–33.7%) and control ( $\overline{x}$ = 17.8%, 95% CI = 10.5%–30.0%) plots in any year. We do not recommend predator removal be continued in Alberta parklands due to its ineffectiveness at improving duck nest survival at the local scale. Full article

The Prairie Pothole Region (PPR) is known for its hydrologically complex landscape with a large number of pothole wetlands. However, most watershed-scale hydrologic models that are applied in this region are incapable of representing the dynamic nature of contributing area and fill-spill processes affected by pothole wetlands. The inability to simulate these processes represents a critical limitation for operators and flood forecasters and may hinder the management of large reservoirs. We used a modified version of the soil water assessment tool (SWAT) model capable of simulating the dynamics of variable contributing areas and fill-spill processes to assess the impact of climate change on upstream inflows into the Shellmouth reservoir (also called Lake of the Prairie), which is an important reservoir built to provide multiple purposes, including flood and drought mitigation. We calibrated our modified SWAT model at a daily time step using SUFI-2 algorithm within SWAT-CUP for the period 1991–2000 and validated for 2005–2014, which gave acceptable performance statistics for both the calibration (KGE = 0.70, PBIAS = −13.5) and validation (KGE = 0.70, PBIAS = 21.5) periods. We then forced the calibrated model with future climate projections using representative concentration pathways (RCPs; 4.5, 8.5) for the near (2011–2040) and middle futures (2041–2070) of multiple regional climate models (RCMs). Our modeling results suggest that climate change will lead to a two-fold increase in winter streamflow, a slight increase in summer flow, and decrease spring peak flows into the Shellmouth reservoir. Investigating the impact of climate change on the operation of the Shellmouth reservoir is critically important because climate change could present significant challenges to the operation and management of the reservoir. Full article

Extensive land use changes and uncertainties arising from climate change in recent years have contributed to increased flood magnitudes in the Canadian Prairies and threatened the vulnerabilities of many small and indigenous communities. There is, thus, a need to create modernized flood risk management tools to support small and rural communities’ preparations for future extreme events. In this study, we developed spatial flood information for an indigenous community in Central Saskatchewan using LiDAR based DEM and a spatial modeling tool, the wetland DEM ponding model (WDPM). A crucial element of flood mapping in this study was community engagement in data collection, scenario description for WDPM, and flood map validation. Community feedback was also used to evaluate the utility of the modelled flood outputs. The results showed the accuracy of WDPM outputs could be improved not only with the quality of DEM but also with additional community-held information on contributing areas (watershed information). Based on community feedback, this accessible, spatially-focused modeling approach can provide relevant information for community spatial planning and developing risk management strategies. Our study found community engagement to be valuable in flood modeling and mapping by: providing necessary data, validating input data through lived experiences, and providing alternate scenarios to be used in future work. This research demonstrates the suitability and utility of LiDAR and WDPM complemented by community participation for improving flood mapping in the Prairie Pothole Region (PPR). The approach used in the study also serves as an important guide for applying transdisciplinary tools and methods for establishing good practice in research and helping build resilient communities in the Prairies. Full article

Land surface phenologies and seasonalities in the US Prairie Pothole Region (PPR) were characterized using land surface variables derived from the coarse spatial resolution (25 km) Advanced Microwave Scanning Radiometer (AMSR) blended data for 2003 to 2016 linked with the optically based USDA NASS Crop Data Layer (CDL) at a much finer spatial resolution. Two transects of AMSR pixels—one in east-central North Dakota and the other in eastern South Dakota—were selected for analysis. The AMSR data were grouped earlier (2003–2005, 2007) and later (2013–2016) to emphasize temporal change and to avoid data discontinuity in 2011–2012 and a major drought in 2006. The nonparametric Mann-Kendall trend test on the CDL data revealed that area in grasslands and wetlands strongly decreased in both transects, while corn and soybean coverage strongly increased. In crop-dominated sites, the AMSR vegetation optical depth (VOD) time series caught the early spring growth, ploughing, and crop growth and senescence. In contrast, the VOD time series at grassland dominated sites exhibited a lower peak but extended growth period. Crop-dominated sites had significantly higher amplitude VODs in both periods and transects. Based on the paired two-sample t-test, neither the peak VOD amplitude nor the peak VOD timing measured in accumulated growing degree-days was significantly different between temporal groups in the North Dakota transect. In contrast, in South Dakota, both the peak VOD amplitude and its timing were significantly different with shifts to later peak timing during the 2013–2016 period. In addition, in South Dakota but not North Dakota, there were significantly earlier shifts in the timing of peak growing degree-days and peak precipitation water vapor. Both spatial and temporal changes in AMSR land surface variables are linked to shifts in land cover along the South Dakota transect as revealed in the CDL data. More research is required to understand the dynamics evident in the passive microwave time series. Full article

Hydrologic margins of wetlands are narrow, transient zones between inundated and dry areas. As water levels fluctuate, the dynamic hydrology at margins may impact wetland greenhouse gas (GHG) fluxes that are sensitive to soil saturation. The Prairie Pothole Region of North America consists of millions of seasonally-ponded wetlands that are ideal for studying hydrologic transition states. Using a long-term GHG database with biweekly flux measurements from 88 seasonal wetlands, we categorized each sample event into wet to wet (W→W), dry to wet (D→W), dry to dry (D→D), or wet to dry (W→D) hydrologic states based on the presence or absence of ponded water from the previous and current event. Fluxes of methane were 5-times lower in the D→W compared to W→W states, indicating a lag ‘ramp-up’ period following ponding. Nitrous oxide fluxes were highest in the W→D state and accounted for 20% of total emissions despite accounting for only 5.2% of wetland surface area during the growing season. Fluxes of carbon dioxide were unaffected by transitions, indicating a rapid acclimation to current conditions by respiring organisms. Results of this study highlight how seasonal drying and re-wetting impact GHGs and demonstrate the importance of hydrologic transitions on total wetland GHG balance. Full article