Daily Time Step Research Articles

Optimization of a leaf wetness duration model

Characterization of LWD (Leaf Wetness Duration) is essential when simulating the spread of phytopathogenic fungi. No standard for leaf wetness measurement exists and a wide range of sensors and models are currently available for estimating LWD. While the vast majority of models use hourly climate data (temperature, relative humidity, etc.) this time step is not widely available in historical records. It is also seldom available in spatially disaggregated projected (21st century) climatic data. Our study aims to develop a new method for using temperature and humidity on a daily time step to simulate leaf wetness duration. The principle behind our model consists in reconstructing hourly temperature and relative humidity based on optimized equations with the bootstrap statistical method for the studied area. Then hourly simulated data are used to estimate the daily duration of leaf wetness. The sensitivity of this process to daily and hourly temperature and relative humidity is assessed. The impact of this model on simulations of potential infections of grapevine (Vitis vinifera L.) by powdery mildew, using a key equation within a mechanistic model that simulates the pathogen's (Erysiphe necator) primary contaminations was evaluated. Results show that the error in simulating LWD and its impact on the potential intensity of the primary contamination of powdery mildew with daily climate data is low. This study has enabled us to set up an optimized modelling chain, which could be readily reproduced in different regions provided existing observational datasets enable suitable parameterization.

Geohydrology of a Reference Mediterranean Catchment (Cilento UNESCO Geopark, Southern Italy)

In this paper, we studied the geo-hydrological structure and behavior of a reference catchment, located in the Cilento UNESCO Global Geopark, southern Italy, representative of the hilly, terrigenous and forested headwaters of the Mediterranean eco-region. Based on detailed hydrogeological and hydro-geomorphological surveys and geomorphometric analysis, starting in 2012, a hydro-chemical monitoring activity at the catchment and sub-catchment scale started, and a hydro-chemical dataset was progressively recorded at daily and sub-hourly time steps. Based on this dataset, the authors performed an original procedure to identify different runoff components, derived by applying cascade mass balance filtering. The integration of hydrological and geomorphological approaches allowed us to obtain an interesting conceptualization of the storm flow generation using hydro-chemical signatures related to different runoff components produced during the increasing–decreasing cycle of the flood event magnitude. The hydro-system activated progressively different runoff sources (i.e., groundwater, riparian corridor, hillslope and hollow) and involved various mechanisms (i.e., groundwater ridging, saturation-excess, infiltration-excess and soil pipe exfiltration). The geo-hydrological conceptualization was validated using a hysteresis Q-EC loop analysis performed on selected events that showed how hysteretic indices could be used to characterize the events in respect to their origins, mechanisms and pathways in similar catchments.

Temporal Analysis of Daily and 10 Minutes of Rainfall of Poprad Station in Eastern Slovakia

The aim of this paper is the application of temporal analysis of daily and 10 min of rainfall data from Poprad station, located in Eastern Slovakia. There are two types of data used in the analysis, firstly, a daily time step data, manually collected between the years 1951 and 2018 and secondly, 10 min of data, automatically collected between the years 2000 and 2018. For proper comparability, the automatically collected data has been recalculated to the daily form. After a comparison of the sets of data, manually collected daily data has been used in further analysis. The main analysis can be divided into two sections. The first section consists of basic statistics (mean, standard deviation, etc.) and the second section of descriptive statistics, where the subjects of examination were trend, stationarity, homogeneity, periodicity and noise. The results of the basic statistics outlined trend behavior in the data meaning that the annual total rainfall for the period 1951–2018 is slightly increasing but the further investigation supported by the methods of descriptive statistics refuted this thesis. The number of rainy days is decreasing but maximum rainfall intensity is increasing year by year, indicating that total rainfall is happening in lesser and lesser days, with an increase in the number of 0 rainfall days. The results demonstrated no presence of the trend or only a weak trend in daily time step, but a significant increasing trend in annual rainfall. Tests of stationarity proved that the data are stationary and, therefore, suitable for any hydrologic analysis. The tests of homogeneity showed no breakpoints in the data. The interesting result was demonstrated by the periodicity test, which showed exactly a 365.25 days’ period, while 0.25 indicates a leap year. As a summary for the Poprad station, there is no tendency of increasing of daily average rainfall, but slight increasing trend of total annual rainfall, the summer season has the highest ratio on total precipitation per year, September and October are the months with the highest numbers of days without rain.

A method to measure hydrologic restoration attributed to low impact development by computing similarity between runoff frequency spectra

Low impact development is to restore natural hydrology in the urban environment. Thus, hydrologic characterization and hydrologic restoration measurement are crucial to low impact development research. The present study uses runoff frequency spectrum to present years of daily runoff events for characterizing flow regime, and develops a method to quantify similarity between runoff frequency spectra for measuring hydrologic restoration. The method was applied to case study of rainwater harvesting of a roof across five climate patterns with annual precipitation from 465.1 to 1807.9 mm/y. 26–30 years of daily runoff data were obtained by continuous mass balance simulation at daily time step that considered stochastic end-use water demand/usage of tanks. For comparison, similarity of total runoff amounts (St) and similarity of runoff frequency spectra (Sd) between undeveloped and developed scenarios were computed to measure hydrologic restoration. Maximum St = 1 was found to be always achievable and only attained by a single rainwater tank size. Maximum Sd = 0.34–0.78, which could be achieved by a size range larger than that with St = 1. Compared with natural condition, total cumulative frequencies of rainwater tank with maximum Sd were declined by 59.2–84.3%. The proposed method solves the problem of quantitative comparison of runoff frequency spectra with different frequencies and lengths, which has advantages of: 1) quantifying the extent of hydrologic restoration at daily temporal resolution, 2) finding a trade-off between reduction of roof runoff intensity and maintenance of natural runoff frequency, and 3) supporting decision-making on strategies to restore natural flow regime in the urban environment as much as possible.

A robust approach for calibrating a daily rainfall-runoff model to monthly streamflow data

Development of robust approaches for calibrating daily rainfall-runoff models to monthly streamflow data is of major practical interest. Such approaches would enable widely used hydrological modelling platforms that operate at daily time step to be applied in practical situations where precipitation is available at the daily scale, but observed streamflow is available only at the monthly scale (e.g. predicting inflows into large dams). This study compares the performance of a hydrological model running at daily time step (GR4J) that is calibrated against daily and monthly streamflow data using a wide range of metrics: fit of the daily and monthly flow duration curve, daily and monthly pattern metrics, and long-term bias. The comparison is undertaken for 508 Australian catchments, two evaluation periods and four objective functions (including sum-of-squared-errors of Box-Cox transformed streamflow and the Kling-Gupta efficiency). Monthly calibration performs similar or better than daily calibration in a majority of sites and periods in terms of bias and fit of the flow duration curve. This result holds even when the flow duration curve is computed at the daily time step, which constitutes a major finding of this study. However, performance of monthly calibration is worse than daily calibration for daily pattern metrics such as Nash-Sutcliffe efficiency in a majority of sites and periods. This performance loss can be reduced significantly by using regionalised values for the flow-timing parameter of GR4J. Similar results are obtained for other pattern metrics and all objective functions. These findings suggest that monthly calibration of rainfall-runoff models to daily-rainfall/monthly-streamflow is a viable alternative to daily calibration when no daily streamflow data are available.

The mango tree – blossom gall midge system: toward in silico assessment of management practices

Mango (Mangifera indica L.), a major fruit production in tropical and subtropical regions, is facing many production constraints. Mango yield is irregular across years, fruit quality is heterogeneous at harvest, and mango tree exhibits phenological asynchronisms within and between trees that result in long periods with phenological stages susceptible to pests and diseases. Among them, the mango blossom gall midge (BGM, Procontarinia mangiferae Felt) is a major pest of mango which can cause significant yield losses by damaging mango inflorescences. A mango-BGM model is currently developed from experimental data. Its final objective will be in silico assessment of BGM management levers (e.g., manipulation of mango phenology to synchronize flowering and soil mulching during flowering, used as physical barrier to break the BGM life-cycle). The mango-BGM model simulates the dynamics of inflorescence and BGM populations of an orchard at a daily time-step during the period of mango flowering. The orchard is structured into three zones (or patches) according to applied mulching treatments. In a first approach, the model is defined at the patch scale and considers: i) age-structured inflorescence population dynamics within each patch, accounting for natural development and BGM-induced mortality of inflorescences; ii) stage-structured BGM population dynamics within each patch, differentiating the effect of mulching treatments on the BGM life-cycle for each patch; and iii) orchard colonization and movements of BGM adults between patches, both driven by inflorescence abundance in each patch. The model was parameterized from existing knowledge and experimental data collected in Reunion Island on 'Cogshall' cultivar. In a further step, virtual experiments will be performed with the model to assess the effects of management levers on mango flowering and subsequent fruit yield, according to exogenous pest pressure. The on-going modeling approach and preliminary results are presented and discussed.

A Channel Network Model for Sediment Dynamics Over Watershed Management Time Scales

AbstractA mountain watershed network model is presented for use in decadal to centurial estimation of source‐to‐sink sediment dynamics. The model requires limited input parameters and can be effectively applied over spatial scales relevant to management of reservoirs, lakes, streams, and watersheds (1–100 km2). The model operates over a connected stream network of Strahler‐ordered segments. The model is driven by streamflow from a physically based hydrology model and hillslope sediment supply from a stochastic mass wasting algorithm. For each daily time step, segment‐scale sediment mass balance is computed using bedload and suspended load transport equations. Sediment transport is partitioned between grain size fractions for bedload as gravel and sand, and for suspended load as sand and mud. Bedload and suspended load can deposit and re‐entrain at each segment. We demonstrated the model in the Elwha River Basin, upstream of the former Glines Canyon dam, over the dam's historic 84‐year lifespan. The model predicted the lifetime reservoir sedimentation volume within the uncertainty range of the measured volume (13.7–18.5 million m3) for 25 of 28 model instances. Gravel, sand, and mud fraction volumes were predicted within measurement uncertainty ranges for 18 model instances. The network model improved the prediction of sediment yields compared to at‐a‐station sediment transport capacity relations. The network model also provided spatially and temporally distributed information that allowed for inquiry and understanding of the physical system beyond the sediment yields at the outlet. This work advances cross‐disciplinary and application‐oriented watershed sediment yield modeling approaches.

Comparison of generalized non-data-driven lake and reservoir routing models for global-scale hydrologic forecasting of reservoir outflow at diurnal time steps

Abstract. Large-scale hydrologic forecasts should account for attenuation through lakes and reservoirs when flow regulation is present. Globally generalized methods for approximating outflow are required but must contend with operational complexity and a dearth of information on dam characteristics at global spatial scales. There is currently no consensus on the best approach for approximating reservoir release rates in large spatial scale hydrologic forecasting, particularly at diurnal time steps. This research compares two parsimonious reservoir routing methods at daily steps: Döll et al. (2003) and Hanasaki et al. (2006). These reservoir routing methods have been previously implemented in large-scale hydrologic modeling applications and have been typically evaluated seasonally. These routing methods are compared across 60 reservoirs operated by the U.S. Army Corps of Engineers. The authors vary empirical coefficients for both reservoir routing methods as part of a sensitivity analysis. The method proposed by Döll et al. (2003) outperformed that presented by Hanasaki et al. (2006) at a daily time step and improved model skill over most run-of-the-river conditions. The temporal resolution of the model influences model performances. The optimal model coefficients varied across the reservoirs in this study and model performance fluctuates between wet years and dry years, and for different configurations such as dams in series. Overall, the method proposed by Döll et al. (2003) could enhance large-scale hydrologic forecasting, but can be subject to instability under certain conditions.

Daily denitrification rates in floodplains under contrasting pedo-climatic and anthropogenic contexts: modelling at the watershed scale

Floodplains play a crucial role in water quality regulation via denitrification. This biogeochemical process reduces nitrate (NO3−), with aquifer saturation, organic carbon (OC) and N availability as the main drivers. To accurately describe the denitrification in the floodplain, it is necessary to better understand nitrate fluxes that reach these natural bioreactors and the transformation that occurs in these surface areas at the watershed scale. At this scale, several approaches tried to simulate denitrification contribution to nitrogen dynamics in study sites. However, these studies did not consider OC fluxes influences, hydrological dynamics and temperature variations at a daily time step. This paper focuses on a new model that allows insights on nitrate, OC, discharge and temperature influences on daily denitrification for each water body. We used a process-based deterministic model to estimate daily alluvial denitrification in different watersheds showing various pedo-climatic conditions. To better understand global alluvial denitrification variability, we applied the method to three contrasting catchments: The Amazon for tropical zones, the Garonne as representative of the temperate climate and the Yenisei for cold rivers. The Amazon with a high discharge, frequent flooding and warm temperature, leads to aquifers saturation, and stable OC concentrations. Those conditions favour a significant loss of N by denitrification. In the Garonne River, the low OC delivery limits the denitrification process. While Arctic rivers have high OC exports, the low nitrate concentrations and cold temperature in the Yenisei River hinder denitrification. We found daily alluvial denitrification rates of 73.0 ± 6.2, 4.5 ± 1.4 and 0.7 ± 0.2 kgN ha−1 y−1 during the 2000–2010 period for the Amazon, the Garonne and the Yenisei respectively. This study quantifies the floodplains influence in the water quality regulation service, their contribution to rivers geochemical processes facing global changes and their role on nitrate and OC fluxes to the oceans.

SSM-iCrop2: A simple model for diverse crop species over large areas

Crop models are essential in undertaking large scale estimation of crop production of diverse crop species, especially in assessing food availability and climate change impacts. In this study, an existing model (SSM, Simple Simulation Models) was adapted to simulate a large number of plant species including orchard species and perennial forages. Simplification of some methods employed in the original model was necessary to deal with limited data availability for some of the plant species to be simulated. The model requires limited, readily available input information. The simulations account for plant phenology, leaf area development and senescence, dry matter accumulation, yield formation, and soil water balance in a daily time step. Parameterization of the model for new crops/cultivars is easy and straight-forward. The resultant model (SSM-iCrop2) was parameterized and tested for more than 30 crop species of Iran using numerous field experiments. Tests showed the model was robust in the predictions of crop yield and water use. Root mean square of error as percentage of observed mean for yield was 18% for grain field crops, 14% for non-grain crops 14% for vegetables and 28% for fruit trees.

Verification of runoff volume, peak discharge and sediment yield simulated using the ACRU model for bare fallow and sugarcane fields

The Agricultural Catchments Research Unit (ACRU) model is a daily time step physical-conceptual agrohydrological model with various applications, design hydrology being one of them. Model verification is a measure of model performance and streamflow, soil water content and sediment yield simulated by the ACRU model have been extensively verified against observed data in southern Africa and internationally. The primary objective of this study was to verify simulated runoff volume, peak discharge and sediment yield against observed data from small catchments, under both bare fallow conditions and sugarcane production, which were located at La Mercy in South Africa. The study area comprised 4 research catchments, 101, 102, 103 and 104, monitored both under bare fallow conditions and sugarcane production, with different management practices per catchment. Observed data comprised: daily rainfall, maximum and minimum temperature, A-pan evaporation and runoff for the period 1978–1995, and peak discharge and sediment yield for the period 1984–1995. The data were checked for errors and and inconsistent records excluded from analysis. Runoff volume, peak discharge and sediment yield were simulated with the ACRU model and verified against the respective observed data. In general, the correlations between observed and simulated daily runoff volumes and peak discharge were acceptable (i.e. slopes of regression lines close to unity, R2 ≥ 0.6 and the Nash–Sutcliffe coefficient of efficiency close to unity). Similarly, the correlation between observed and simulated sediment yield was also good. From the results obtained, it is concluded that the ACRU model is suitable for the simulation of runoff volume, peak discharge and sediment yield from catchments under both bare fallow and sugarcane land cover in South Africa.

Verification of runoff volume, peak discharge and sediment yield simulated using the ACRU model for bare fallow and sugarcane fields

The Agricultural Catchments Research Unit (ACRU) model is a daily time step physical-conceptual agrohydrological model with various applications, design hydrology being one of them. Model verification is a measure of model performance and streamflow, soil water content and sediment yield simulated by the ACRU model have been extensively verified against observed data in southern Africa and internationally. The primary objective of this study was to verify simulated runoff volume, peak discharge and sediment yield against observed data from small catchments, under both bare fallow conditions and sugarcane production, which were located at La Mercy in South Africa. The study area comprised 4 research catchments, 101, 102, 103 and 104, monitored both under bare fallow conditions and sugarcane production, with different management practices per catchment. Observed data comprised: daily rainfall, maximum and minimum temperature, A-pan evaporation and runoff for the period 1978–1995, and peak discharge and sediment yield for the period 1984–1995. The data were checked for errors and and inconsistent records excluded from analysis. Runoff volume, peak discharge and sediment yield were simulated with the ACRU model and verified against the respective observed data. In general, the correlations between observed and simulated daily runoff volumes and peak discharge were acceptable (i.e. slopes of regression lines close to unity, R2 ≥ 0.6 and the Nash–Sutcliffe coefficient of efficiency close to unity). Similarly, the correlation between observed and simulated sediment yield was also good. From the results obtained, it is concluded that the ACRU model is suitable for the simulation of runoff volume, peak discharge and sediment yield from catchments under both bare fallow and sugarcane land cover in South Africa.

A study on three different hydropower operation rules by monthly and daily time steps

Operation simulation models are developed for monthly and daily time steps for computing the hydroelectric energy and its financial benefits in an economic life by three different operation policies: steady-rate, three-shift and pumped-storage rules. The pump is operated during the night and consumes low-cost energy. The resulting computer programs, three on monthly and three on daily steps, are applied to the Yamula dam – which is a fairly large dam generating energy, located in the Inland Anatolia region of Turkey – over a period of 35 years using the gauged daily stream flows and daily pan evaporations. The results indicate that the pumped storage is more profitable than the other two rules aside from the intangible benefits of regulating the within-day fluctuations of demand for electrical energy. Another result is that both the average annual energy and the financial benefits given by the three rules computed by the monthly time steps are about 1−2% greater than those given by the daily time steps. This study is the first one comparing all these three operation schemes quantitatively in a realistic way both in monthly and daily time steps.

Informing hydrological models of poorly gauged river catchments – A parameter regionalization and calibration approach

Development of robust hydrologic-hydrodynamic simulation models is challenging, especially in regions, where in-situ observation data are scarce. Parameter calibration is often a necessary and data-demanding step. Moreover, good calibration performance does not guarantee predictive skill in neighboring geographic regions or new time periods and scenarios. A robust calibration strategy is necessary and must apply an informed parameter regionalization approach, which can transfer parameter values from gauged to ungauged subcatchments, whilst accounting for data availability and quality. In this study, a calibration strategy combining a parameter transfer framework based on catchment similarities with a holistic calibration against hydrological signatures is presented to obtain reliable simulations at all relevant locations within a catchment. The approach is demonstrated for three African river catchments: the Tana, the Upper Niger and the Semliki catchments.A rainfall-runoff model based on Budyko’s concept of limits with up to 11 calibration parameters and a daily simulation time step is used, coupled with a Muskingum routing scheme. Each river catchment is subdivided into so-called hydrological response units (HRU) based on climatic and physiographic characteristics. Multi-mission satellite remote sensing observations are used for the HRU classification: terrain slope derived from the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) and the publicly available European Space Agency (ESA) Climate Change Initiative (CCI) land cover map. Subcatchments within each HRU share the same parameters. The number of units is constrained by the number of in-situ stations available. The calibration strategy is a catchment-scale, multi-objective approach.The method improved the overall model performance compared to a simpler, nearest-neighbor regionalization method. In particular, spatial patterns of the hydrological response are more reasonable and performance is improved at validation stations, highlighting the importance of appropriate parameter regionalization within nested catchments. With this method, a wider range of currently available remote sensing data (elevation, precipitation, land cover, etc.) can be exploited in hydrological model development and calibration.

Tracer‐Aided Modeling in the Low‐Relief, Wet‐Dry Tropics Suggests Water Ages and DOC Export Are Driven by Seasonal Wetlands and Deep Groundwater

AbstractOur understanding of how wet‐dry tropical catchments process water and solutes remains limited. In this study, we attempt to gain understanding of water and dissolved organic carbon (DOC) transport, storage, and mixing in a 126 km2 catchment of northern Australia. We developed a coupled, tracer‐aided, conceptual rainfall‐runoff model (SAVTAM) that simultaneously calculates water, isotope, and DOC‐based processes at a daily time step. The semidistributed model can account for the marked hydrological distinction between savanna woodlands and adjacent seasonal wetlands. Using the calibrated model, we tracked the fluxes and derived the age of water in fluxes and storages. Model output matched the seasonal variability, controlled by seasonal rainfall, which switched on and off water and carbon flow pathways from the savanna to seasonal wetlands and ultimately to the perennial river. Such hydrological connectivity is modulated by the karst aquifer system that continuously contributes older waters (decades to century old) to maintain relatively stable and older streamflow during the dry season (average stream water age = 9.7 to 16.2 years). Such older waters occur despite a rapid, monsoon‐driven streamflow response. The DOC fluxes were largely sourced from the wetland and riparian forest that transported DOC in the order of 1.9 t C km−2 year−1 to the stream, which was on average 90% of the total simulated DOC exports of 2 t C·km−2·year−1. We conclude that coupled simulation of water and biogeochemistry is necessary to generate a more complete picture of catchment functioning, particularly in the tropics.

Optimizing multifunctional agroecosystems in irrigated dryland agriculture to restore soil carbon – Experiments and modelling

Irrigated dryland agroecosystems could become more sustainable if crop and soil management enhanced soil organic carbon (SOC). We hypothesized that combining high inputs from cover crops with no-tillage will increase long-term SOC stocks. Caatinga shrublands had been cleared in 1972 for arable crops and palm plantations before implementing field experiments on Mango and Melon systems (established in 2009 and 2012, respectively). Each of the two experiments were managed with no-till (NT) or conventional till (CT), and three types of cover cropping, either a plant mixture of 75% (PM1) or 25% (PM2) legumes, or spontaneous vegetation (SV). The RothC model was used with a daily timestep to simulate the soil moisture dynamics and C turnover for this dry climate. Carbon inputs were between 2.62 and 5.82 Mg C ha−1 year−1 and increased the depleted SOC stocks by 0.08 to 0.56 Mg C ha−1 year−1. Scenarios of continuous biomass inputs of ca. 5 Mg C ha−1 year−1 for 60 years are likely to increase SOC stocks in the mango NT beyond the original Caatinga SOC by between 19.2 and 20.5 Mg C ha−1. Under CT similar inputs would increase SOC stocks only marginally above depletion (2.75 to 2.47 Mg C ha−1). Under melon, annual carbon inputs are slightly greater (up to 5.5 Mg C ha−1 year−1) and SOC stocks would increase on average by another 8% to 22.3 to 20.6 Mg C ha−1 under NT and by 8 Mg C ha−1 under CT. These long-term simulations show that combining NT with high quality cover crops (PM1, PM2) would exceed SOC stocks of the initial Caatinga within 20 and 25 years under irrigated melon and mango cultivation, respectively. These results present a solution to reverse prior loss of SOC by replacing CT dryland agriculture with irrigated NT plus high input cover crops agroecosystems.

Impact of Climate Change on the Spatiotemporal Distribution of Stream Flow and Sediment Yield of Darbandikhan Watershed, Iraq

The impact of climate change on stream flow and sediment yield in Darbandikhan Watershed is an important challenge facing the water resources in Diyala River, Iraq. This impact was investigated using five Global Circulation Models (GCM) based climate change projection models from the A1B scenario of medium emission. The Soil and Water Assessment Tool (SWAT) was used to compute the temporal and spatial distribution of streamflow and sediment yield of the study area for the period 1984 to 2050. The daily-observed flow recorded in Darbandikhan Dam for the period from 1984 to 2013 was used as a base period for future projection. The initial results of SWAT were calibrated and validated using SUFI-2 of the SWAT-CUP program in daily time step considering the values of the Nash-Sutcliffe Efficiency (NSE) coefficient of determination (R2) as a Dual objective function. Results of NSE and R2 during the calibration (validation) periods were equal to 0.61 and 0.62(0.53 and 0.68), respectively. In addition, the average future prediction for the five climate models indicated that the average yearly flow and sediment yield in the watershed would decrease by about 49% and 44%, respectively, until the year 2050 compared with these of the base period from 1984 to 2013. Moreover, spatial analysis shows that 89.6 % and 90 % of stream flow and sediment come from the Iranian part of Darbandikhan watershed while the remaining small percent comes from Iraq, respectively. However, the middle and southern parts of Darbandikhan Watershed contribute by most of the stream...

Relating hydroclimatic change to streamflow, baseflow, and hydrologic partitioning in the Upper Rio Grande Basin, 1980 to 2015

Understanding how changing climatic conditions affect streamflow volume and timing is critical for effective water management. In the Rio Grande Basin of the southwest U.S., decreasing snowpack, increasing minimum temperatures, and decreasing streamflow have been observed in recent decades, but the effects of hydroclimatic changes on baseflow, or groundwater discharge to streams, have not been investigated. In this study, we determine how trends in precipitation, snowpack accumulation, and snowmelt rate relate to total streamflow, baseflow, and the hydrologic partitioning of baseflow and runoff at 12 sites in the Upper Rio Grande Basin (URGB) during 1980 to 2015. Total streamflow was partitioned into baseflow and runoff components at a daily time step using conductivity-mass-balance hydrograph separation. Trends in annual total streamflow, baseflow, runoff, baseflow index, precipitation, snowmelt rate, and peak snow water equivalent (SWE) were evaluated from 1980 to 2015 using the non-parametric Mann-Kendall trend test. Results indicate that baseflow forms a large component of total streamflow, contributing an average of 49% of total discharge upstream of Albuquerque, NM. During 1980 to 2015, decreasing trends in total streamflow occurred at 9 of 12 sites and were almost always associated with decreases in baseflow, suggesting that baseflow volumes can respond to changing climatic and anthropogenic conditions within decades. Decreasing snowmelt rates were more frequently associated with decreases in baseflow and total streamflow than were decreases in precipitation and peak SWE, highlighting the importance of snowmelt rate as a process controlling streamflow generation. If snow accumulation and snowmelt rates continue to decrease in the future, results indicate that total streamflow and baseflow volumes will decline, and that baseflow will become a larger fraction of total streamflow in the URGB.

Can model-based data products replace gauge data as input to the hydrological model?

Abstract Hydrological models require accurate and representative meteorological inputs for better prediction of discharge and hence, the efficient management of water resources. Numerical weather prediction model-based reanalysis data products on the catchment scale are becoming available, and they could be an alternative input data for hydrological models. This study focuses on the applicability of a set of model-based data as input to hydrological models used in inflow predictions for operational hydropower production planning of three hydropower systems in middle Norway. First, the study compared the data products with gauge measurements. Then, Hydrologiska Byråns Vattenbalansavdelning (HBV) models of the three catchments were calibrated with three different meteorological datasets (model-based, gauge and observational gridded) separately using a Monte Carlo approach. It was found that the correlation between the model-based and gauged precipitation was highly variable among stations, and daily values showed a better correlation than hourly. The performance of model-based input data with daily timestep was nearly as good as the gauge or gridded data for the model calibration. Further, the annual simulated flow volume using the model-based data was satisfactory as similar to the gauge or gridded input data, which indicate that model-based data can be a potential data source for long-term operational hydropower production planning.

Climate Change Impacts on Reservoir Inflow in the Prairie Pothole Region: A Watershed Model Analysis

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.