Short-term climate change influence on surface water quality impacts from agricultural activities

Climate change is a global phenomenon that directly affects agriculture by altering crop yield, nutritional quality, pests, and plant diseases. The North Aegean Basin located in Turkey has considerable agricultural importance due to its fertile soils. Agricultural activities have increased significantly and uncontrollably in the last decade, resulting in dramatic changes in nitrate and phosphorus levels in surface water within the watershed. Changes in climatic conditions have the potential to impact the quantity and quality of water resources. Best management practices (BMPs) are presently utilized as a planning tool to enhance the quality of water resources. To develop policies in this regard, it is necessary to evaluate the effectiveness of BMPs. To this end, this study aims to investigate the potential effect of climate change on the surface water quality of the North Aegean Basin. For the period between 2010 and 2030, global climate data retrieved from Concentration Pathway (RCP) scenarios 4.5 and 8.5 and regionally downscaled were used to feed the Soil and Water Assessment Tool (SWAT) model. The various potential BMP scenarios were developed and simulated in the hydrological model by considering the effects of climate change. The RCP4.5 scenario reduced the precipitation by 15.11%, while the RCP8.5 scenario reduced the precipitation by 10.97%. Decreased precipitation also affected the runoff and the nutrient loads and concentrations. As a result of the RCP4.5 simulation, TP and TN concentrations increased by 24.42% and 58.45%, respectively, in the IST_KEN014 station. Improvements were observed in TN and TP concentrations with the effect of applied BMP simulations. Also, the results revealed that the applied BMP scenarios may contribute to considerable reductions in nutrient loads. Considering the RCP4.5 scenario, BMPs reduced TN loads in the basin by 2.42-10.97%, while reducing TP loads by around 3.60-16.81%. Considering the RCP8.5 scenario, the BMPs reduced the TN loads in the basin between 2.21 and 10.04%, while they reduced the TP loads between 3.57 and 16.67%.

Spatial and temporal variability of climate change impacts on ecosystem services in small agricultural catchments using the Soil and Water Assessment Tool (SWAT)

Climate change and anthropogenic activities alter the ecosystem which affects the ecosystem services (ES) associated with it. Therefore, the objective in this study is to quantify the impact of climate change on different regulation and provisioning ecosystem services. For this, we propose a modelling framework to simulate the impact of climate change on streamflow, nitrate loads, erosion, and crop yield in terms of ES indices for two agricultural catchments (Schwesnitz and Schwabach) located in Bavaria, Germany. The agro-hydrologic model Soil and Water Assessment Tool (SWAT) is used to simulate the considered ES in past (1990-2019), near future (2030-2059) and far future (2070-2099) climatic conditions. Three different bias-corrected (Representative Concentration Pathway, RCP 2.6, 4.5, and 8.5) climate projections from five different climate models retrieved from the Bavarian State Office for Environment (∼5 km) are used in this research to simulate the impact of climate change on ES. The developed SWAT models were calibrated for the major crops (1995 to 2018) present in the respective watersheds as well as for daily streamflow (1995 to 2008), which gave promising results with good PBIAS and Kling-Gupta Efficiency. The impact of climate change on erosion regulation, food and feed provisioning, and water quantity and water quality regulation were quantified in terms of indices. When using the ensemble of the five climate models, no significant impact on ES was seen due to climate change. Furthermore, the impact of climate change on different ES services from the two catchment is different. The findings of this study will be valuable for devising suitable management practices for sustainable water management at the catchment level to cope with climate change.

Quantifying the impact of climate variability and human activities on streamflow variation in Taoer River Basin, China

Climate variability and human activity are the two driving forces that alter the hydrological cycle and spatiotemporal distribution of water resources. Using the Taoer River Basin (TRB) as an example, this study analyzed the impacts of climate variability and human activities on streamflow discharge in various periods and the resulting hydrological alterations. First, historical streamflow data were divided into four periods (baseline period and altered periods 1, 2, and 3). Based on the proposed basic identification framework, four assessment methods (the hydrological sensitivity method, distributed hydrological model, linear regression model, and runoff restoring computation) are used and provided relatively consistent estimates of streamflow attribution. Climate variability is the driving factor for streamflow changes, and the relative contributions in altered periods 1, 2, and 3 are 81% (+ 50.34 mm), 68% (+ 13.37 mm), and 53% (-19.23 mm), respectively. In addition, climate variability and reservoir construction have different impacts on the hydrological regime at different periods, and reservoir regulation's effect on the hydrological regime depends on climatic conditions. Combined with this case study, we further discuss the necessity of breakpoint selection and period subdivision in the attribution of streamflow changes, and analyze the applicability of different methods with current ideas for improvement. This study not only has practical significance for water resource planning and adaptive policy formulation in the TRB but also provides a useful reference for similar studies.

Using SWAT Model to Assess the Impacts of Land Use and Climate Changes on Flood in the Upper Weihe River, China

Flood disasters have occurred frequently in recent years, but there is no consensus on the mechanism and influencing factors. Taking the upper reaches of Weihe River Basin as a case in Western China, a soil and water assessment tool (SWAT) model was established to quantitatively simulate the impact of land use and climate change on runoff changes, while 4 extreme land-use scenarios and 24 temperature and precipitation scenarios assumptions were proposed to simulate the response of runoff to land use and climate changes. The SWAT simulation results showed that the sensitivity parameters affecting the model simulation were the CANMX, CN2, SOL_K, CH_N2, and SOL_AWC. The correlation index R2 and the efficiency coefficient ENS of the upper Weihe River were both in the range of 0.75–0.78, the relative error PS between the simulated results and the measured runoff was below 10%, suggesting the good applicability of the SWAT model in this study area. Using the improved SWAT model to simulate the peak runoff (flood) simulation value is generally smaller than the measured value, and the absolute value of the error is less than 6%. The expansion of wasteland increased the runoff by over 90% on average, the expansion of cultivated land increased the runoff by 8% on average, and the expansion of woodland and grassland increased the surface runoff by 6% on average. When the precipitation decreased by 25% and the temperature increased by 22%, the smallest runoff was obtained in the simulation. Accordingly, when the precipitation increased by 25% and the temperature decreased by 22%, the maximum annual runoff was obtained. By decomposing the contribution rate of human activities and climate change to runoff, it showed that the contribution rate of human activities to the reduction of runoff was greater than that of climate change. This study can provide scientific reference for the simulation and prediction of future floods.

Evaluation of Ecosystem-Based Adaptation Measures for Sediment Yield in a Tropical Watershed in Thailand

Ecosystem-based adaptation (EbA) can potentially mitigate watershed degradation problems. In this study, various EbA measures were evaluated using a bio-physical model called the Soil and Water Assessment Tool (SWAT), in a small, forested watershed named Hui Ta Poe, in the northeastern region of Thailand. The developed watershed model was first used to investigate the effect of various degraded watersheds due to land-use changes on the sediment yield in the study area. The most degraded watershed produced an annual average sediment yield of 13.5 tons/ha. This degraded watershed was then used to evaluate the effectiveness of various EbA measures such as reforestation, contouring, filter strips, and grassed waterways in reducing the sediment yield. Under all individual and combined EbA scenarios analyzed, there was a significant reduction in sediment yield; however, the maximum reduction of 88% was achieved with a combined scenario of reforestation, grassed waterways, and filter strips. Reforestation alone was found to be the second-best option, which could reduce the sediment yield by 84%. Contouring alone was the least effective, with a reduction in sediment yield of only 23%. This study demonstrates the usefulness of implementing EbA measures for sediment management strategies to address watershed degradation, which is a severe problem across the globe.

Evaluation of Multi-Satellite Precipitation Datasets and Their Error Propagation in Hydrological Modeling in a Monsoon-Prone Region

This study comprehensively evaluates eight satellite-based precipitation datasets in streamflow simulations on a monsoon-climate watershed in China. Two mutually independent datasets—one dense-gauge and one gauge-interpolated dataset—are used as references because commonly used gauge-interpolated datasets may be biased and unable to reflect the real performance of satellite-based precipitation due to sparse networks. The dense-gauge dataset includes a substantial number of gauges, which can better represent the spatial variability of precipitation. Eight satellite-based precipitation datasets include two raw satellite datasets, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Climate Prediction Center MORPHing raw satellite dataset (CMORPH RAW); four satellite-gauge datasets, Tropical Rainfall Measuring Mission 3B42 (TRMM), PERSIANN Climate Data Record (PERSIANN CDR), CMORPH bias-corrected (CMORPH CRT), and gauge blended datasets (CMORPH BLD); and two satellite-reanalysis-gauge datasets, Multi-Source Weighted-Ensemble Precipitation (MSWEP) and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS). The uncertainty related to hydrologic model physics is investigated using two different hydrological models. A set of statistical indices is utilized to comprehensively evaluate the precipitation datasets from different perspectives, including detection, systematic, random errors, and precision for simulating extreme precipitation. Results show that CMORPH BLD and MSWEP generally perform better than other datasets. In terms of hydrological simulations, all satellite-based datasets show significant dampening effects for the random error during the transformation process from precipitation to runoff; however, these effects cannot hold for the systematic error. Even though different hydrological models indeed introduce uncertainties to the simulated hydrological processes, the relative hydrological performance of the satellite-based datasets is consistent in both models. Namely, CMORPH BLD performs the best, which is followed by MSWEP, CMORPH CRT, and TRMM. PERSIANN CDR and CHIRPS perform moderately well, and two raw satellite datasets are not recommended as proxies of gauged observations for their worse performances.

Climate Change Impacts on Soil Erosion and Sediment Yield in a Watershed

This study analyzed the influence of climate change on sediment yield variation, sediment transport and erosion deposition distribution at the watershed scale. The study was based on Gaoping River basin, which is among the largest basins in southern Taiwan. To carry out this analysis, the Physiographic Soil Erosion Deposition (PSED) model was utilized. Model results showed a general increase in soil erosion and deposition volume under the A1B-S climate change scenario. The situation is even worsened with increasing return periods. Total erosion volume and total sediment yield in the watershed were increased by 4–25% and 8–65%, respectively, and deposition volumes increased by 2–23%. The study showed how climate change variability would influence the watershed through increased sediment yields, which might even worsen the impacts of natural disasters. It has further illustrated the importance of incorporating climate change into river management projects.

Flooding Urban Landscapes: Analysis Using Combined Hydrodynamic and Hydrologic Modeling Approaches

The frequency and severity of floods have been found to increase in recent decades, which have adverse effects on the environment, economics, and human lives. The catastrophe of such floods can be confronted with the advance prediction of floods and reliable analyses methods. This study developed a combined flood modeling system for the prediction of floods, and analysis of associated vulnerabilities on urban infrastructures. The application of the method was tested on the Blue River urban watershed in Missouri, USA, a watershed of historical significance for flood impacts and abundance of data availability for such analyses. The combined modeling system included two models: hydrodynamic model HEC-RAS (Hydrologic Engineering Center—River Analysis System) and hydrologic model SWAT (Soil and Water Assessment Tool). The SWAT model was developed for the watershed to predict time-series hydrograph data at desired locations, followed by the setup of HEC-RAS model for the analysis and prediction of flood extent. Both models were calibrated and validated independently using the observed data. The well-calibrated modeling setup was used to assess the extent of impacts of the hazard by identifying the flood risk zones and threatened critical infrastructures in flood zones through inundation mapping. Results demonstrate the usefulness of such combined modeling systems to predict the extent of flood inundation and thus support analyses of management strategies to deal with the risks associated with critical infrastructures in an urban setting. This approach will ultimately help with the integration of flood risk assessment information in the urban planning process.

Surface Depression and Wetland Water Storage Improves Major River Basin Hydrologic Predictions

Surface water storage in small yet abundant landscape depressions-including wetlands and other small waterbodies-is largely disregarded in conventional hydrologic modeling practices. No quantitative evidence exists of how their exclusion may lead to potentially inaccurate model projections and understanding of hydrologic dynamics across the world's major river basins. To fill this knowledge gap, we developed the first-ever major river basin-scale modeling approach integrating surface depressions and focusing on the 450,000-km2 Upper Mississippi River Basin (UMRB) in the United States. We applied a novel topography-based algorithm to estimate areas and volumes of ~455,000 surface depressions (>1 ha) across the UMRB (in addition to lakes and reservoirs) and subsequently aggregated their effects per subbasin. Compared to a "no depression" conventional model, our depression-integrated model (a) improved streamflow simulation accuracy with increasing upstream abundance of depression storage, (b) significantly altered the spatial patterns and magnitudes of water yields across 315,000 km2 (70%) of the basin area, and (c) provided realistic spatial distributions of rootzone wetness conditions corresponding to satellite-based data. Results further suggest that storage capacity (i.e., volume) alone does not fully explain depressions' cumulative effects on landscape hydrologic responses. Local (i.e., subbasin level) climatic and geophysical drivers and downstream flowpath-regulating structures (e.g., reservoirs and dams) influence the extent to which depression storage volume in a subbasin causes hydrologic effects. With these new insights, our study supports the integration of surface depression storage and thereby catalyzes a reassessment of current hydrological modeling and management practices for basin-scale studies.

Analysis of alternative climate datasets and evapotranspiration methods for the Upper Mississippi River Basin using SWAT within HAWQS

This study reports the application of Soil and Water Assessment Tool (SWAT) within the Hydrologic and Water Quality System (HAWQS) on-line platform, for the Upper Mississippi River Basin (UMRB). The UMRB is an important ecosystem located in the north central U.S. that is experiencing a range of ecological stresses. Specifically, testing of SWAT was performed for: (1) Hargreaves (HG) and Penman-Monteith (PM) PET methods, and (2) Livneh, National Climatic Data Center (NCDC) and Parameter-elevation Regressions on Independent Slopes Model (PRISM) climate datasets. The Livneh-PM combination resulted in the highest average annual water yield of 380.6 mm versus the lowest estimated water yield of 193.9 mm for the Livneh-HG combination, in response to 23-year uncalibrated simulations. Higher annual ET and PET values were predicted with HG method versus the PM method for all three weather datasets in response to the uncalibrated simulations, due primarily to higher HG-based estimates during the growing season. Based on these results, it was found that the HG method is the preferred PET option for the UMRB. Initial calibration of SWAT was performed using the Livneh data and HG method for three Mississippi River main stem gauge sites, which was followed by spatial validation at 10 other gauge sites located within the UMRB stream network. Overall satisfactory results were found for the calibration and validation gauge sites, with the majority of R2 values ranging between 0.61 and 0.82, Nash-Sutcliffe modeling efficiency (NSE) values ranging between 0.50 and 0.79, and Kling-Gupta efficiency (KGE) values ranging between 0.61 and 0.84. The results of an additional experimental suite of six scenarios, which represented different combinations of climate data sets and calibrated parameters, revealed that suggested statistical criteria were again satisfied by the different scenario combinations. Overall, the PRISM data exhibited the strongest reliability for the UMRB.

SWAT ungauged: Water quality modeling in the Upper Mississippi River Basin

Improving model performance in ungauged basins has been a chronic challenge in watershed model application to understand and assess water quality impacts of agricultural conservation practices, land use change, and climate adaptation measures in large river basins. Here, we evaluate a modified version of SWAT2012 (referred to as SWAT-EC hereafter), which integrates an energy balanced soil temperature module (STM) and the CENTRUY-based soil organic matter algorithm, for simulating water quality parameters in the Upper Mississippi River Basin (UMRB), and compare it against the original SWAT2012. Model evaluation was performed for simulating streamflow, sediment, and nitrate-N (NO₃-N) and total nitrogen (TN) loadings at three stations near the outlets of UMRB. The model comparison was conducted without parameter calibration in order to assess their performance under ungauged conditions. The results indicate that SWAT-EC outperformed SWAT2012 for stream flow and NO₃-N and TN loading simulation on both monthly and annual scales. For sediment, SWAT-EC performed better than SWAT2012 on a monthly time step basis, but no noticeable improvement was found at the annual scale. In addition, the performance of the uncalibrated SWAT-EC was comparable to other calibrated SWAT models reported in previous publications with respect to sediment and NO₃-N loadings. These findings highlight the importance of advancing process representation in physically-based models to improve model credibility, particularly in ungauged basins.

Assessment of Wetland Restoration and Climate Change Impacts on Water Balance Components of the Heeia Coastal Wetland in Hawaii

Hydrological modeling is an important tool that can be used to assess water resources’ availability and sustainability that are necessary for food security and ecological health of coastal regions. In this study, we assessed the impacts of land use and climate changes on water balance components (WBCs) of the Heeia coastal wetland. We developed a Soil and Water Assessment Tool (SWAT) model to capture the unique characteristics of the Hawaiian Islands, including its volcanic soil’s nature and high initial infiltration rates. We used the sequential uncertainty fitting algorithm to assess the sensitivity and uncertainty of WBCs under different climate change scenarios. Results of the statistical analysis of daily streamflow simulations showed that the model performance was within the generally acceptable criteria. Under future climate scenarios, rainfall change was the determinant factor most negatively impacting WBCs. Recharge and baseflow components had the highest sensitivity to the combined effects of land use and climate changes, especially during dry season. The uncertainty analysis indicated that the streamflow is projected to slightly increase by the middle of 21st century, but expected to decline by 40% during the late 21st century of Representative Concentration Pathways (RCP) 8.5.

Modeling the Impact of Climate Change on Water Availability in the Zarrine River Basin and Inflow to the Boukan Dam, Iran

The impacts of climate change on the water availability of Zarrine River Basin (ZRB), the headwater of Lake Urmia, in western Iran, with the Boukan Dam, are simulated under various climate scenarios up to year 2029, using the SWAT hydrological model. The latter is driven by meteorological variables predicted from MPI-ESM-LR-GCM (precipitation) and CanESM2-GCM (temperature) GCM models with RCP 2.6, RCP 4.5 and RCP 8.5 climate scenarios, and downscaled with Quantile Mapping (QM) bias-correction and SDSM, respectively. From two variants of QM employed, the Empirical-CDF-QM model decreased the biases of raw GCM- precipitation predictors particularly strongly. SWAT was then calibrated and validated with historical (1981–2011) ZR-streamflow, using the SWAT-CUP model. The subsequent SWAT-simulations for the future period 2012–2029 indicate that the predicted climate change for all RCPs will lead to a reduction of the inflow to Boukan Dam as well as of the overall water yield of ZRB, mainly due to a 23–35% future precipitation reduction, with a concomitant reduction of the groundwater baseflow to the main channel. Nevertheless, the future runoff-coefficient shows a 3%, 2% and 1% increase, as the −2% to −26% decrease of the surface runoff is overcompensated by the named precipitation decrease. In summary, based on these predictions, together with the expecting increase of demands due to the agricultural and other developments, the ZRB is likely to face a water shortage in the near future as the water yield will decrease by −17% to −39%, unless some adaptation plans are implemented for a better management of water resources.

Agricultural Water Productivity-Based Hydro-Economic Modeling for Optimal Crop Pattern and Water Resources Planning in the Zarrine River Basin, Iran, in the Wake of Climate Change

For water-stressed regions/countries, like Iran, improving the management of agricultural water-use in the wake of climate change and increasingly unsustainable demands is of utmost importance. One step further is then the maximization of the agricultural economic benefits, by properly adjusting the irrigated crop area pattern to optimally use the limited amount of water available. To that avail, a sequential hydro-economic model has been developed and applied to the agriculturally intensively used Zarrine River Basin (ZRB), Iran. In the first step, the surface and groundwater resources, especially, the inflow to the Boukan Dam, as well as the potential crop yields are simulated using the Soil Water Assessment Tool (SWAT) hydrological model, driven by GCM/QM-downscaled climate predictions for three future 21th-century periods under three climate RCPs. While in all nine combinations consistently higher temperatures are predicted, the precipitation pattern are much more versatile, leading to corresponding changes in the future water yields. Using the basin-wide water management tool MODSIM, the SWAT-simulated water available is then optimally distributed across the different irrigation plots in the ZRB, while adhering to various environmental/demand priority constraints. MODSIM is subsequently coupled with CSPSO to optimize (maximize) the agro-economic water productivity (AEWP) of the various crops and, subsequently, the net economic benefit (NEB), using crop areas as decision variables, while respecting various crop cultivation constraints. Adhering to political food security recommendations for the country, three variants of cereal cultivation area constraints are investigated. The results indicate considerably-augmented AEWPs, resulting in a future increase of the annual NEB of ~16% to 37.4 Million USD for the 65%-cereal acreage variant, while, at the same time, the irrigation water required is reduced by ~38%. This NEB-rise is achieved by augmenting the total future crop area in the ZRB by about 47%—indicating some deficit irrigation—wherefore most of this extension will be cultivated by the high AEWP-yielding crops wheat and barley, at the expense of a tremendous reduction of alfalfa acreage. Though presently making up only small base acreages, depending on the future period/RCP, tomato- and, less so, potato- and sugar beet-cultivation areas will also be increased significantly.

Iowa Stream Nitrate, Discharge and Precipitation: 30-Year Perspective

We evaluated Iowa Department of Natural Resources nitrate (NO₃-N) and US Geological Survey hydrological data from 1987 to 2016 in nine agricultural watersheds to assess how transport of this pollutant has changed in the US state of Iowa. When the first 15 years of the 30-year water-quality record is compared to the second 15 years (1987-2001 and 2002-2016), three different metrics used to quantify NO₃-N transport all indicate levels of this pollutant are increasing. Yield of NO₃-N (kg ha^-1) averaged 18% higher in the second 15 years, while flow-weighted average concentrations (mg L^-1) were 12% higher. We also introduced the new metric of NO₃-N yield (g ha^-1) per mm precipitation to assess differences between years and watersheds, which averaged 21 g NO₃-N ha^-1 per 1 mm of precipitation across all watersheds and was 13% higher during the second half of the record. These increases of NO₃-N occurred within a backdrop of increasing wetness across Iowa, with precipitation and discharge levels 8 and 16% higher in the last half of the record, indicating how NO₃-N transport is amplified by increasing precipitation levels. The implications of this are that in future climate scenarios where rainfall is more abundant, detaining water and increasing evapotranspiration within the cropping system will be necessary to control NO₃-N losses. Land use changes that include use of cover crops, living mulches, and perennial plants should be expanded to improve water quality and affect the water balance within agricultural basins.

Hydrological Modeling of Climate Change Impacts in a Tropical River Basin: A Case Study of the Cauto River, Cuba

The soil and water assessment tool (SWAT) model was applied for the first time in Cuba to assess the potential impacts of climate change on water availability in the Cauto River basin. The model was calibrated (and validated) for the 2001–2006 (2007–2010) period at a monthly timescale in two subbasins La Fuente and Las Coloradas, representative of middle and upper sections of the Cauto basin; the calibrated models showed good performance. The output available for the regional climate Model RegCM4.3 was used to force the calibrated SWAT models to simulate a baseline (1970–2000) period and near-future (2015–2039) hydrologic regimes under the representative concentration pathway (RCP) 8.5 emission scenario. The future projections suggest regional increases of 1.5 °C in mean annual temperature and a 38% decrease in mean annual precipitation in the subbasins. These changes translate to possible reductions in the annual streamflow of up to 61% with respect to the baseline period, whereas the aquifer recharge in the basin is expected to decrease up to 58%, with a consequent reduction of groundwater flow, especially during the boreal summer wet season. These projection scenarios should be of interest to water resources managers in tropical regions.

Combined and synergistic effects of climate change and urbanization on water quality in the Wolf Bay watershed, southern Alabama

This study investigated potential changes in flow, total suspended solid (TSS) and nutrient (nitrogen and phosphorous) loadings under future climate change, land use/cover (LULC) change and combined change scenarios in the Wolf Bay watershed, southern Alabama, USA. Four Global Circulation Models (GCMs) under three Special Report Emission Scenarios (SRES) of greenhouse gas were used to assess the future climate change (2016-2040). Three projected LULC maps (2030) were employed to reflect different extents of urbanization in future. The individual, combined and synergistic impacts of LULC and climate change on water quantity/quality were analyzed by the Soil and Water Assessment Tool (SWAT). Under the "climate change only" scenario, monthly distribution and projected variation of TSS are expected to follow a pattern similar to streamflow. Nutrients are influenced both by flow and management practices. The variation of Total Nitrogen (TN) and Total Phosphorous (TP) generally follow the flow trend as well. No evident difference in the N:P ratio was projected. Under the "LULC change only" scenario, TN was projected to decrease, mainly due to the shrinkage of croplands. TP will increase in fall and winter. The N:P ratio shows a strong decreasing potential. Under the "combined change" scenario, LULC and climate change effect were considered simultaneously. Results indicate that if future loadings are expected to increase/decrease under any individual scenario, then the combined change will intensify that trend. Conversely, if their effects are in opposite directions, an offsetting effect occurs. Science-based management practices are needed to reduce nutrient loadings to the Bay.

Past, present and future land use changes and their impact on water balance

Landuse change influences the water balance of a region affecting the available water along with the change in the evapotranspiration (ET). The major objectives of this study are to assess the landuse change and its impact on the water balance of the study area, which is a part of the Narmada river basin in Madhya Pradesh, India. Landuse changes of 1990, 2000 and 2011 have been analyzed and the Markov Chain model has been used to predict decadal change of 2020, 2030, 2040 and 2050 landuse. The influence of the past, present and future landuse change on water balance has been analyzed with the SWAT (Soil and Water Analysis Tool) model in the study area. The effect of changes are shown in 12 different sub-watersheds of the area, reflecting an increased water yield (runoff, including ground-water outflow) and surface runoff but decreased ET, which is due to change in the curve number (CN) values (79.85 in 1990 to 84.63 in 2050). Increased CN value in different sub-watersheds of the region has been observed due to a reduction in the vegetation areas, and increase in the agricultural land and settlements. This has caused an increased runoff and decreased ET. The water yield has increased by 6.98% from 1990 to 2011 (1.92 CN increase) and by 17.5% as projected in the 2050 (4.78 CN increase). The actual ET decreases by 3.37% from 1990 to 2011 and by 8.40% in 2050. Simulation with the SWAT using landuse change showed reduction in ET and increased runoff in different sub-watersheds, which needs to be considered in terms of management.

Evaluation of Drought Implications on Ecosystem Services: Freshwater Provisioning and Food Provisioning in the Upper Mississippi River Basin

Drought is one of the most widespread extreme climate events with a potential to alter freshwater availability and related ecosystem services. Given the interconnectedness between freshwater availability and many ecosystem services, including food provisioning, it is important to evaluate the drought implications on freshwater provisioning and food provisioning services. Studies about drought implications on streamflow, nutrient loads, and crop yields have been increased and these variables are all process-based model outputs that could represent ecosystem functions that contribute to the ecosystem services. However, few studies evaluate drought effects on ecosystem services such as freshwater and food provisioning and quantify these services using an index-based ecosystem service approach. In this study, the drought implications on freshwater and food provisioning services were evaluated for 14 four-digit HUC (Hydrological Unit Codes) subbasins in the Upper Mississippi River Basin (UMRB), using three drought indices: standardized precipitation index (SPI), standardized soil water content index (SSWI), and standardized streamflow index (SSI). The results showed that the seasonal freshwater provisioning was highly affected by the precipitation deficits and/or surpluses in summer and autumn. A greater importance of hydrological drought than meteorological drought implications on freshwater provisioning was evident for the majority of the subbasins, as evidenced by higher correlations between freshwater provisioning and SSI12 than SPI12. Food provisioning was substantially affected by the precipitation and soil water deficits during summer and early autumn, with relatively less effect observed in winter. A greater importance of agricultural drought effects on food provisioning was evident for most of the subbasins during crop reproductive stages. Results from this study may provide insights to help make effective land management decisions in responding to extreme climate conditions in order to protect and restore freshwater provisioning and food provisioning services in the UMRB.

Swimming against the tide: resilience of a riverine turtle to recurrent extreme environmental events

Extreme environmental events (EEEs) are likely to exert deleterious effects on populations. From 1996 to 2012 we studied the nesting dynamics of a riverine population of painted turtles (Chrysemys picta) that experienced seven years with significantly definable spring floods. We used capture-mark-recapture methods to estimate the relationships between more than 5 m and more than 6 m flood events and population parameters. Contrary to expectations, flooding was not associated with annual differences in survival, recruitment or annual population growth rates of the adult female segment of the population. These findings suggest that female C. picta exhibit resiliency to key EEE, which are expected to increase in frequency under climate change.

Potential water quality changes due to corn expansion in the Upper Mississippi River Basin

While biofuels may yield renewable fuel benefits, there could be downsides in terms of water quality and other environmental stressors, particularly if corn is relied upon exclusively as the feedstock. The consequences of increased corn production will depend importantly on where (and how) the additional corn is grown, which, in turn, depends on the characteristics of land and its associated profitability. Previous work has relied on rules of thumb for allocating land to increased acreage based on historical land use or other heuristics. Here, we advance our understanding of these phenomena by describing a modeling system that links an economics-driven land use model with a watershed-based water quality model for the Upper Mississippi River Basin (UMRB). This modeling system is used to assess the water quality changes due to increased corn acreage, which is associated with higher relative corn prices. We focus on six scenarios based on six realistic pairs of corn and soybean prices which correspond to a scale of decreasing soybean to corn price ratio. These price-driven land use changes provide estimates of the water quality effects that current biofuel policies may have in the UMRB. Our analysis can help evaluate the costs and environmental consequences associated with implementation strategies for the biofuel mandates of the new energy bill. The amounts of total N and P delivered to the outlet of the UMRB (located at Grafton, Illinois, USA) rise as corn production becomes more intensive in the region. Our results indicate that a 14.4% in corn acreage in the watershed due to corn intensification in the most economically profitable locations would result in a 5.4% increase in total nitrogen loads and in a 4.1% increase in total phosphorus loads at Grafton. Our most aggressive scenario, driven by high but not out of reach crop prices, results in about a 57% increase in corn acreage with a corresponding 18.5% increase in N and 12% increase in P. These are somewhat conservative increases in nutrients, compared to those of previous studies, likely due to our focus on cultivated cropland which is already heavily fertilized.