The safe application of farm dairy effluent (FDE) to land has proven to be a challenge for dairy farmers and regulatory authorities throughout New Zealand. Poorly performing FDE systems can have deleterious effects on water quality because contaminants such as phosphorus, nitrogen and faecal microbes enter receiving waters with minimal attenuation by soil. We present a decision framework that supports good management of effluent, particularly during its application to land. The framework considers how FDE management can be tailored to account for soil and landscape features of a location that pose varying levels of contaminant transport risk. High risk soils and landscapes are vulnerable to direct losses via preferential and/or overland flow pathways and include sloping land (e.g. slopes greater than 7 degrees) and soils with mole drainage, coarse structure, poor natural drainage or low surface infiltration rates. Soil types that are well-drained with fine structure typically exhibit matrix flow characteristics and represent a relatively low risk of direct contaminant loss following FDE application. Our framework provides guidance on FDE application timings, rates and depths to different landform and soil types so that direct losses of contaminants to water are minimal and the opportunity for plant uptake of nutrients is enabled. Some potential limitations for using the framework include the potentially severe effects of animal treading damage during wet conditions that can reduce soil hydrological function and consequently increase the risk of overland flow of applied FDE. The spatial distribution of such treading damage should be considered in the framework's application. Another limitation is our limited understanding of the effects of soil hydrophobicity on FDE infiltration and application of the framework.

Soil detachment capacity (D-c) is a crucial indicator for quantifying erosion intensity. However, the combined actions of freeze-thaw and water flow complicate the erosion process, leaving the variation mechanism of D-c under this condition systematically unexplored. This study examined five loess soils from a seasonal freeze-thaw area. The mechanism driving changes in Dcwas quantified through freeze-thaw simulation combined with flow scouring tests, and a D-c prediction model was established. The results revealed that the shear strength (tau(m)), cohesion (Coh), and internal friction angle (phi) in silt loam were higher than in sandy loam. After freeze-thaw cycles (FTC), tau(m), Coh, and phi of the five loess soils decreased by 1.02-1.37, 1.07-9.15, and 0.92-1.05 times, respectively. As FTC increased, tau(m) and Coh gradually stabilized, while phi showed minimal fluctuation, indicating that FTC had a cumulative effect on the deterioration of soil mechanical properties. During FTC, D-c in Wuzhong sandy loam was the largest, being 1.14-3.24 times greater than in other soils, suggesting a significant main effect of soil type on D-C variation, with a contribution rate of 19.27 %. Dceventually stabilized with increasing, indicating a critical FTC of around 10 for its impact on D-c. Compared to unfrozen soils, D-c increased by 33.69 %- 102.40 % under the combined effects of freeze-thaw and water flow, clarifying that FTC aggravated soil instability. Effective stream power was the optimum hydraulic parameter, contributing the most to Dc(45.94 %). FTC (6.41 %) and initial soil moisture content (8.59 %) were less influential, as FTC initially degraded soil properties, and then the combined action with water flow intensified soil damage, causing the role of freeze-thaw factors to be obscured by other variables. A Dcprediction model using a general flow intensity index estimated well D-c, with both R-2 and NSE at 0.94. Model performance comparison emphasized the need for validation when extending the application range beyond development conditions. These findings provide new insights into the detachment mechanisms of different textured soils under compound freeze-thaw and hydrodynamic influence in freeze-thaw region.

Soil detachment capacity (Dc) is an important parameter used to determine erosion intensity in physical-processbased erosion models. Freeze-thaw affects soil detachment processes by altering the mechanical properties of soil; however, due to the compound action of freeze-thaw and runoff on D-c, quantifying the impact of seasonal freeze-thaw on D-c remains challenging. A series of experiments with six freeze-thaw cycles (FTC), six initial soil moisture contents (SMC), three slope gradients, and five flow discharges were conducted to investigate the effect of freeze-thaw and hydrodynamic characteristics on D-c. The results showed that soil shear strength (tau(m)), cohesion (Coh), and internal friction angle (phi) gradually tended to become stable with increasing FTC, indicating that repeated FTC had a cumulative impact on soil mechanical properties, and there was a critical FTC between 5 and 7. When FTC rose from 1 to 15, the reduction in tau m, Coh, and phi was 0.03-23.96%, 2.63-75.21%, and - 5.70-19.24%, respectively, which increased with an increasing SMC, suggesting that the deterioration effect of FTC on soil mechanical properties was promoted by increasing SMC. During alternating FTC, the relative range and variation coefficient of D-c were 2.21-2.43 and 67.87-75.72%, respectively, indicating that D-c was highly sensitive to FTC. Furthermore, D-c increased by 2.37-71.22% after 15 FTC. Alternating freeze-thaw weakened the soil resistance to detachment. Moreover, the promoting effect of FTC on D-c intensified with an increasing SMC, indicating that the variation in D-c was strongly affected by SMC during FTC. A prediction model (R-2=0.955, RRMSE=14.99%) was established to quantify the influence of freeze-thaw and hydrodynamic characteristics on D-c. The explanation rate of variables in the D-c prediction equation was quantitated: the explanation rate of stream power (64.3%) was higher than that of FTC (10.02%) and SMC (3.92%), suggesting that the impact of freeze-thaw on D-c was covered by hydrodynamic characteristics. Further validation is required for the prediction equations when applied beyond the range of construction conditions.

A process-based, spatially distributed hydrological model was developed to quantitatively simulate the energy and mass transfer processes and their interactions within arctic regions (arctic hydrological and thermal model, ARHYTHM). The model first determines the flow direction in each element, the channel drainage network and the drainage area based upon the digital elevation data. Then it simulates various physical processes: including snow ablation, subsurface flow, overland flow and channel flow routing, soil thawing and evapotranspiration. The kinematic wave method is used for conducting overland flow and channel flow routing. The subsurface flow is simulated using the Darcian approach. The energy balance scheme was the primary approach used in energy-related process simulations (snowmelt and evapotranspiration), although there are options to model snowmelt by the degree-day method and evapotranspiration by the Priestley-Taylor equation. This hydrological model simulates the dynamic interactions of each of these processes and can predict spatially distributed snowmelt, soil moisture and evapotranspiration over a watershed at each time step as well as discharge in any specified channel(s). The model was applied to Imnavait watershed (about 2.2 km(2)) and the Upper Kuparuk River basin (about 146 km(2)) in northern Alaska. Simulated results of spatially distributed soil moisture content, discharge at gauging stations, snowpack ablations curves and other results yield reasonable agreement, both spatially and temporally, with available data sets such as SAR imagery-generated soil moisture data and field measurements of snowpack ablation, and discharge data at selected points. The initial timing of simulated discharge does not compare well with the measured data during snowmelt periods mainly because the effect of snow damming on runoff was not considered in the model. Results from the application of this model demonstrate that spatially distributed models have the potential for improving our understanding of hydrology for certain settings. Finally, a critical component that led to the performance of this modelling is the coupling of the mass and energy processes. Copyright (C) 2000 John Wiley & Sons, Ltd.