WRR Comment:基于有限理性假设的农民行为分析

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Comment on “Exploring the Influence of Smallholders’ Perceptions Regarding Water Availability on Crop Choice and Water Allocation Through Socio‐Hydrological Modeling” by Kuil et al. [Water Resource Research, 54, 2580–2604]

First published: 08 March 2019
https://doi.org/10.1029/2018WR023684
A paper has recently been published in Water Resources Research, which explored the influence of smallholder’s perceptions regarding water availability on crop choice and water allocation through social‐hydrological modeling. The present paper attempts to discuss and comment on that paper. The authors have developed a social‐hydrological model, behind which some assumptions of the hydrological aspects (including the omission of deep percolation and the complete separation of transpiration and evaporation for the growing season and the off‐season) are not well justified. Further, a few parameter values seem to be mistakenly presented by the authors. Most importantly, t[……]

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AGWM效率悖论文章

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Published in Agricultural Water Management

Ling Zhang, Qimin Ma, Yanbo Zhao et al.

ABSTRACT: Improving irrigation efficiency is widely believed to be a promising opportunity for large water savings. However, more and more voices have been raised against this idea in recent years. This study investigated the impacts of irrigation efficiency improvement on water use and consumption by combining an agro-economic model with the conceptualization of hydrological pathways. The investigation was conducted under two different conditions, i.e., Case 1: unlimited water supply and restricted irrigatable land, and Case 2: limited water supply and unrestricted irrigatable land. At the scale of the WUU, we found that the water uses could be reduced significantly after improving irrigation efficiency, while the water consumptions would be of similar magnitudes for different irrigation techniques under the condition of Case 1. However, in the condition of Case 2, the water uses would be inelasti[……]

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HP水文影响分离文章

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Published in Hydrological Processes

https://onlinelibrary.wiley.com/doi/abs/10.1002/hyp.13331

Separating climate change and human contributions to variations in streamflow and its components using eight time‐trend methods

Ling Zhang,  Zhuotong Nan, Weizhen Wang, et al.

Abstract

Separating impacts of human activities and climate change on hydrology is essential for watershed and ecosystem management. Many previous studies have focused on the impacts on total streamflow, however, with little attentions paid to its components (i.e., baseflow and surface runoff). This study distinguished the contributions of climate change and human activities to the variations in streamflow, baseflow and surface runoff in the upstream area of the Heihe River Basin, a typical inland river basin in northwest China, by using eight different forms of time‐trend methods. The isolated contributions to streamflow variation were also compared with those obtained by two Budyko‐based approaches. Our result[……]

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Matlab codes for two breakpoint checken

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(1)  累计距平均

data=xlsread(‘test.xlsx’);

data(:,1)=[];

mean_data=mean(data);

diff_streamflow=data(:,1)-mean_data(1);

diff_baseflow=data(:,2)-mean_data(2);

diff_surfq=data(:,3)-mean_data(3);

Sum_streamflow_anomaly=zeros(55,1);

Sum_baseflow_anomaly=zeros(55,1);

Sum_surfq_anomaly=zeros(55,1);

for i=1:55;

Sum_streamflow_anomaly(i)=sum(diff_streamflow(1:i));

Sum_baseflow_anomaly(i)=sum(diff_baseflow(1:i));

Sum_surfq_anomaly(i)=sum(diff_surfq(1:i));

end

years=(1960:2014)’;

xlswrite(‘cumulative_anomaly.xlsx’,[years,Sum_streamflow_anomaly,Sum_baseflow_anomaly,Sum_surfq_anomaly])

通过绘图找到分界点即得到break point

(2)   Pettitt检测

% This code is used to find the change point in a univariate continuous time series

% using Pettitt Test.

%

%

% The test here assumed is two-tailed test. The hypothesis are as follow:

%  H (Null Hypothesis): There is no change point in the series

%  H(Alternative Hypothesis): There is a change point in the se[……]

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